{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"model.ipynb","provenance":[],"mount_file_id":"176ztTbXuwYF0zUA3VjEW1AsJRdkfPG2a","authorship_tag":"ABX9TyPgiCneXyrdZKtLQd2QpwDP"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"id":"i9sSQLdfDSZt","executionInfo":{"status":"ok","timestamp":1602850044111,"user_tz":-330,"elapsed":2109,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"19b89f0f-8684-4ddd-ae20-d445574d073c","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["cd /content/drive/My Drive/Loan Prediction"],"execution_count":107,"outputs":[{"output_type":"stream","text":["/content/drive/My Drive/Loan Prediction\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"S-agvot3DvBv","executionInfo":{"status":"ok","timestamp":1602850044112,"user_tz":-330,"elapsed":1587,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["import numpy as np\n","import pandas as pd\n","import matplotlib.pyplot as plt\n"],"execution_count":108,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"B2YCQtLxD8Pr"},"source":["# Load Dataset"]},{"cell_type":"code","metadata":{"id":"RsLH_w6ND0iG","executionInfo":{"status":"ok","timestamp":1602850044112,"user_tz":-330,"elapsed":1456,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data=pd.read_csv('dataset.csv')"],"execution_count":109,"outputs":[]},{"cell_type":"code","metadata":{"id":"Y9-Q4SChECbN","executionInfo":{"status":"ok","timestamp":1602850044113,"user_tz":-330,"elapsed":1406,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"8c1ccfee-95d4-4ab9-feaa-a0465e1312fb","colab":{"base_uri":"https://localhost:8080/","height":232}},"source":["data.head()"],"execution_count":110,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Loan_ID</th>\n","      <th>Gender</th>\n","      <th>Married</th>\n","      <th>Dependents</th>\n","      <th>Education</th>\n","      <th>Self_Employed</th>\n","      <th>ApplicantIncome</th>\n","      <th>CoapplicantIncome</th>\n","      <th>LoanAmount</th>\n","      <th>Loan_Amount_Term</th>\n","      <th>Credit_History</th>\n","      <th>Property_Area</th>\n","      <th>Loan_Status</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>LP001002</td>\n","      <td>Male</td>\n","      <td>No</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>5849</td>\n","      <td>0.0</td>\n","      <td>NaN</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>LP001003</td>\n","      <td>Male</td>\n","      <td>Yes</td>\n","      <td>1</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>4583</td>\n","      <td>1508.0</td>\n","      <td>128.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Rural</td>\n","      <td>N</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>LP001005</td>\n","      <td>Male</td>\n","      <td>Yes</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>Yes</td>\n","      <td>3000</td>\n","      <td>0.0</td>\n","      <td>66.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>LP001006</td>\n","      <td>Male</td>\n","      <td>Yes</td>\n","      <td>0</td>\n","      <td>Not Graduate</td>\n","      <td>No</td>\n","      <td>2583</td>\n","      <td>2358.0</td>\n","      <td>120.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>LP001008</td>\n","      <td>Male</td>\n","      <td>No</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>6000</td>\n","      <td>0.0</td>\n","      <td>141.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["    Loan_ID Gender Married  ... Credit_History Property_Area Loan_Status\n","0  LP001002   Male      No  ...            1.0         Urban           Y\n","1  LP001003   Male     Yes  ...            1.0         Rural           N\n","2  LP001005   Male     Yes  ...            1.0         Urban           Y\n","3  LP001006   Male     Yes  ...            1.0         Urban           Y\n","4  LP001008   Male      No  ...            1.0         Urban           Y\n","\n","[5 rows x 13 columns]"]},"metadata":{"tags":[]},"execution_count":110}]},{"cell_type":"markdown","metadata":{"id":"oWn0xSq-EhEd"},"source":["# EDA"]},{"cell_type":"code","metadata":{"id":"s5aUETHQEF1M","executionInfo":{"status":"ok","timestamp":1602850044113,"user_tz":-330,"elapsed":1257,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data.drop(['Loan_ID'],axis=1,inplace=True)"],"execution_count":111,"outputs":[]},{"cell_type":"code","metadata":{"id":"aa7wsN0oE6Z_","executionInfo":{"status":"ok","timestamp":1602850044114,"user_tz":-330,"elapsed":1152,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"7eb0bc42-f3d1-4655-c16b-9db503c343a4","colab":{"base_uri":"https://localhost:8080/","height":336}},"source":["data.info()"],"execution_count":112,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 614 entries, 0 to 613\n","Data columns (total 12 columns):\n"," #   Column             Non-Null Count  Dtype  \n","---  ------             --------------  -----  \n"," 0   Gender             601 non-null    object \n"," 1   Married            611 non-null    object \n"," 2   Dependents         599 non-null    object \n"," 3   Education          614 non-null    object \n"," 4   Self_Employed      582 non-null    object \n"," 5   ApplicantIncome    614 non-null    int64  \n"," 6   CoapplicantIncome  614 non-null    float64\n"," 7   LoanAmount         592 non-null    float64\n"," 8   Loan_Amount_Term   600 non-null    float64\n"," 9   Credit_History     564 non-null    float64\n"," 10  Property_Area      614 non-null    object \n"," 11  Loan_Status        614 non-null    object \n","dtypes: float64(4), int64(1), object(7)\n","memory usage: 57.7+ KB\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"WjpEMN6EE_2Z","executionInfo":{"status":"ok","timestamp":1602850044115,"user_tz":-330,"elapsed":1087,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"176287f9-b004-4034-bba3-ba29619c77eb","colab":{"base_uri":"https://localhost:8080/","height":284}},"source":["data.describe()"],"execution_count":113,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>ApplicantIncome</th>\n","      <th>CoapplicantIncome</th>\n","      <th>LoanAmount</th>\n","      <th>Loan_Amount_Term</th>\n","      <th>Credit_History</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>614.000000</td>\n","      <td>614.000000</td>\n","      <td>592.000000</td>\n","      <td>600.00000</td>\n","      <td>564.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>5403.459283</td>\n","      <td>1621.245798</td>\n","      <td>146.412162</td>\n","      <td>342.00000</td>\n","      <td>0.842199</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>6109.041673</td>\n","      <td>2926.248369</td>\n","      <td>85.587325</td>\n","      <td>65.12041</td>\n","      <td>0.364878</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>150.000000</td>\n","      <td>0.000000</td>\n","      <td>9.000000</td>\n","      <td>12.00000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>2877.500000</td>\n","      <td>0.000000</td>\n","      <td>100.000000</td>\n","      <td>360.00000</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>3812.500000</td>\n","      <td>1188.500000</td>\n","      <td>128.000000</td>\n","      <td>360.00000</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>5795.000000</td>\n","      <td>2297.250000</td>\n","      <td>168.000000</td>\n","      <td>360.00000</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>81000.000000</td>\n","      <td>41667.000000</td>\n","      <td>700.000000</td>\n","      <td>480.00000</td>\n","      <td>1.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["       ApplicantIncome  CoapplicantIncome  ...  Loan_Amount_Term  Credit_History\n","count       614.000000         614.000000  ...         600.00000      564.000000\n","mean       5403.459283        1621.245798  ...         342.00000        0.842199\n","std        6109.041673        2926.248369  ...          65.12041        0.364878\n","min         150.000000           0.000000  ...          12.00000        0.000000\n","25%        2877.500000           0.000000  ...         360.00000        1.000000\n","50%        3812.500000        1188.500000  ...         360.00000        1.000000\n","75%        5795.000000        2297.250000  ...         360.00000        1.000000\n","max       81000.000000       41667.000000  ...         480.00000        1.000000\n","\n","[8 rows x 5 columns]"]},"metadata":{"tags":[]},"execution_count":113}]},{"cell_type":"code","metadata":{"id":"f2SvkgMKFCyk","executionInfo":{"status":"ok","timestamp":1602850044995,"user_tz":-330,"elapsed":969,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"2e6b77d8-2f60-4bae-e190-91d4f970b8da","colab":{"base_uri":"https://localhost:8080/","height":235}},"source":["data.isnull().sum()"],"execution_count":114,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Gender               13\n","Married               3\n","Dependents           15\n","Education             0\n","Self_Employed        32\n","ApplicantIncome       0\n","CoapplicantIncome     0\n","LoanAmount           22\n","Loan_Amount_Term     14\n","Credit_History       50\n","Property_Area         0\n","Loan_Status           0\n","dtype: int64"]},"metadata":{"tags":[]},"execution_count":114}]},{"cell_type":"code","metadata":{"id":"Ff3sTIKtF7rR","executionInfo":{"status":"ok","timestamp":1602850046496,"user_tz":-330,"elapsed":2233,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"305e680a-4738-4103-b1c4-16d8b0850cd7","colab":{"base_uri":"https://localhost:8080/","height":351}},"source":["import seaborn as sns\n","sns.countplot(data['Loan_Status'],hue=data['Gender'])"],"execution_count":115,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n","  FutureWarning\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7fe8fce125f8>"]},"metadata":{"tags":[]},"execution_count":115},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAYUAAAEICAYAAACwDehOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAZxElEQVR4nO3de5QV5Z3u8e8jcvE2KtA6SAPdjoxIC8OlbTWecyQQRTFH0ON4iSY9wQQ9y8uYM5pJTIiO0UmcMcmJhoUhS4NGI7pAlDHGiaKY6KjQLQQbLwEdkOagENROvMDQ8Dt/7OpyA027sbv2brqfz1p7de233qr9272Ah3qr6i1FBGZmZgD7lLoAMzPrPBwKZmaWciiYmVnKoWBmZimHgpmZpRwKZmaW2jerHUvqA/wW6J18ztyIuE7SbOBkoCnp+ncRsUySgB8Dk4APk/YX2/qM/v37R0VFRUbfwMysa6qvr/9jRJS1ti6zUAC2AOMj4n1JPYFnJP06WXdNRMzdqf/pwNDkdTwwM/m5WxUVFdTV1XVw2WZmXZukNbtbl9nwUeS8n7ztmbzaulNuMnB3st3zwCGSBmRVn5mZ7SrTcwqSekhaBmwAHo+IF5JVN0laLulHknonbQOBtXmbNyZtZmZWJJmGQkRsi4hRQDlQI+lY4JvAMOA4oC/wj3uyT0nTJNVJqtu4cWOH12xm1p1leU4hFRHvSXoKOC0ibkmat0j6OXB18n4dMChvs/Kkbed9zQJmAVRXV3viJrNubuvWrTQ2NrJ58+ZSl9Lp9OnTh/Lycnr27FnwNllefVQGbE0CYT/gFOBmSQMiYn1ytdEUoCHZZAFwuaQ55E4wN0XE+qzqM7OuobGxkYMOOoiKigpy/6wYQESwadMmGhsbqaysLHi7LI8UBgB3SepBbpjqgYh4RNKTSWAIWAZcmvR/lNzlqKvIXZL65QxrM7MuYvPmzQ6EVkiiX79+7Okwe2ahEBHLgdGttI/fTf8ALsuqHjPruhwIrfs0vxff0WxmZimHgplZ4u233+YLX/gCRx55JGPHjuXEE09k/vz57d7vokWL+PznP98BFWavKFcfdWZjr7m71CV0GvX/+qVSl2BWMhHBlClTqK2t5Ze//CUAa9asYcGCBUWvpbm5mX33Lc0/zz5SMDMDnnzySXr16sWll16atg0ZMoQrrriCbdu2cc0113DccccxcuRIfvrTnwK5I4Bx48ZxzjnnMGzYMC688EJaHnH82GOPMWzYMMaMGcODDz6Y7vODDz5g6tSp1NTUMHr0aB5++GEAZs+ezZlnnsn48eOZMGFCEb/5jrr9kYKZGcCKFSsYM2ZMq+vuuOMODj74YJYsWcKWLVs46aSTOPXUUwFYunQpK1as4IgjjuCkk07i2Wefpbq6mq9+9as8+eSTHHXUUZx33nnpvm666SbGjx/PnXfeyXvvvUdNTQ2f+9znAHjxxRdZvnw5ffv2zf4L74ZDwcysFZdddhnPPPMMvXr1YsiQISxfvpy5c3PzeDY1NbFy5Up69epFTU0N5eXlAIwaNYrVq1dz4IEHUllZydChQwG46KKLmDVrFgC/+c1vWLBgAbfckruPd/Pmzbz55psAnHLKKSUNBHAomJkBUFVVxbx589L3M2bM4I9//CPV1dUMHjyY2267jYkTJ+6wzaJFi+jdu3f6vkePHjQ3N7f5ORHBvHnzOProo3dof+GFFzjggAM64Ju0j88pmJkB48ePZ/PmzcycOTNt+/DDDwGYOHEiM2fOZOvWrQD84Q9/4IMPPtjtvoYNG8bq1at5/fXXAbjvvvvSdRMnTuS2225Lzz0sXbq0w79LezgUzMzI3ej10EMP8fTTT1NZWUlNTQ21tbXcfPPNfOUrX2H48OGMGTOGY489lksuuaTNI4I+ffowa9YszjjjDMaMGcNhhx2Wrps+fTpbt25l5MiRVFVVMX369GJ8vYKpJa32RtXV1dHeh+z4ktSP+ZJU2xu98sorHHPMMaUuo9Nq7fcjqT4iqlvr7yMFMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlO5rNrEvp6MvMC7lUWxIXXngh99xzD5Cb5XTAgAEcf/zxPPLII7vdbtGiRdxyyy1t9ik2HymYmbXTAQccQENDAx999BEAjz/+OAMHDixxVZ+OQ8HMrANMmjSJX/3qV0BuWosLLrggXbd48WJOPPFERo8ezWc+8xlee+21Xbbf3ZTaxeZQMDPrAOeffz5z5sxh8+bNLF++nOOPPz5dN2zYMH73u9+xdOlSbrjhBq699tpdtm+ZUnvx4sU89dRTXHPNNW3Or5QVn1MwM+sAI0eOZPXq1dx3331MmjRph3VNTU3U1taycuVKJKUT6+Xb3ZTaxZ7Cw6FgZtZBzjzzTK6++moWLVrEpk2b0vbp06fz2c9+lvnz57N69WrGjRu3y7a7m1K72DIbPpLUR9JiSb+XtELSPyXtlZJekLRK0v2SeiXtvZP3q5L1FVnVZmaWhalTp3LdddcxYsSIHdqbmprSE8+zZ89uddvOMqV2lkcKW4DxEfG+pJ7AM5J+Dfwf4EcRMUfS7cDFwMzk57sRcZSk84GbgfN2t3Mzs9aUcrbf8vJyrrzyyl3av/71r1NbW8uNN97IGWec0eq206dP56qrrmLkyJFs376dysrKklyqWpSpsyXtDzwD/G/gV8BfRkSzpBOB6yNioqR/T5afk7Qv8BZQFm0U6KmzO5anzra9kafOblunmjpbUg9Jy4ANwOPA68B7EdHydIpGoOVi3oHAWoBkfRPQL8v6zMxsR5mGQkRsi4hRQDlQAwxr7z4lTZNUJ6lu48aN7a7RzMw+VpT7FCLiPeAp4ETgkGR4CHJhsS5ZXgcMAkjWHwxs2mlXRMSsiKiOiOqysrLMazcz606yvPqoTNIhyfJ+wCnAK+TC4ZykWy3QctveguQ9yfon2zqfYGZmHS/Lq48GAHdJ6kEufB6IiEckvQzMkXQjsBS4I+l/B/ALSauAd4DzM6zNzMxakVkoRMRyYHQr7W+QO7+wc/tm4G+zqsfMzD6Z72g2sy7lzRtGfHKnPTD4Oy99Yp8ePXrscMPaQw89REVFRYfW0aKiooK6ujr69++fyf4dCmZm7bTffvuxbNmyUpfRITxLqplZBurr6zn55JMZO3YsEydOZP369QCMGzeOr33ta1RXV3PMMcewZMkSzj77bIYOHcq3v/3tdPspU6YwduxYqqqqmDVrVqufcc8991BTU8OoUaO45JJL2LZtW7vrdiiYmbXTRx99xKhRoxg1ahRnnXUWW7du5YorrmDu3LnU19czdepUvvWtb6X9e/XqRV1dHZdeeimTJ09mxowZNDQ0MHv27HQivTvvvJP6+nrq6uq49dZbd5hgD3J3Kt9///08++yzLFu2jB49enDvvfe2+7t4+MjMrJ12Hj5qaGigoaGBU045BYBt27YxYMCAdP2ZZ54JwIgRI6iqqkrXHXnkkaxdu5Z+/fpx6623Mn/+fADWrl3LypUr6dfv40keFi5cSH19PccddxyQC6bDDjus3d/FoWBm1sEigqqqKp577rlW1/fu3RuAffbZJ11ued/c3MyiRYt44okneO6559h///0ZN24cmzdv3uUzamtr+d73vtehtXv4yMysgx199NFs3LgxDYWtW7eyYsWKgrdvamri0EMPZf/99+fVV1/l+eef36XPhAkTmDt3Lhs2bADgnXfeYc2aNe2u3UcKZtalFHIJadZ69erF3LlzufLKK2lqaqK5uZmrrrqKqqqqgrY/7bTTuP322znmmGM4+uijOeGEE3bpM3z4cG688UZOPfVUtm/fTs+ePZkxYwZDhgxpV+1FmTo7K546u2N56mzbG3nq7LZ1qqmzzcxs7+JQMDOzlEPBzPZ6e/MweJY+ze/FoWBme7U+ffqwadMmB8NOIoJNmzbRp0+fPdrOVx+Z2V6tvLycxsZG/CTGXfXp04fy8vI92sahYGZ7tZ49e1JZWVnqMroMDx+ZmVnKoWBmZimHgpmZpRwKZmaWciiYmVnKoWBmZqnMQkHSIElPSXpZ0gpJf5+0Xy9pnaRlyWtS3jbflLRK0muSJmZVm5mZtS7L+xSagX+IiBclHQTUS3o8WfejiLglv7Ok4cD5QBVwBPCEpL+OiPY/dNTMzAqS2ZFCRKyPiBeT5T8DrwAD29hkMjAnIrZExH8Cq4CarOozM7NdFeWcgqQKYDTwQtJ0uaTlku6UdGjSNhBYm7dZI22HiJmZdbDMQ0HSgcA84KqI+BMwE/grYBSwHvjBHu5vmqQ6SXWe68TMrGNlGgqSepILhHsj4kGAiHg7IrZFxHbgZ3w8RLQOGJS3eXnStoOImBUR1RFRXVZWlmX5ZmbdTpZXHwm4A3glIn6Y1z4gr9tZQEOyvAA4X1JvSZXAUGBxVvWZmdmusrz66CTgi8BLkpYlbdcCF0gaBQSwGrgEICJWSHoAeJnclUuX+cojM7PiyiwUIuIZQK2serSNbW4CbsqqJjMza5vvaDYzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUpmFgqRBkp6S9LKkFZL+PmnvK+lxSSuTn4cm7ZJ0q6RVkpZLGpNVbWZm1rosjxSagX+IiOHACcBlkoYD3wAWRsRQYGHyHuB0YGjymgbMzLA2MzNrRWahEBHrI+LFZPnPwCvAQGAycFfS7S5gSrI8Gbg7cp4HDpE0IKv6zMxsV0U5pyCpAhgNvAAcHhHrk1VvAYcnywOBtXmbNSZtZmZWJJmHgqQDgXnAVRHxp/x1ERFA7OH+pkmqk1S3cePGDqzUzMwKCgVJCwtpa6VPT3KBcG9EPJg0v90yLJT83JC0rwMG5W1enrTtICJmRUR1RFSXlZUVUr6ZmRWozVCQ1EdSX6C/pEOTK4f6JsNBbQ7tSBJwB/BKRPwwb9UCoDZZrgUezmv/UnIV0glAU94wk5mZFcG+n7D+EuAq4AigHlDS/ifgJ5+w7UnAF4GXJC1L2q4Fvg88IOliYA1wbrLuUWASsAr4EPhy4V/DzMw6QpuhEBE/Bn4s6YqIuG1PdhwRz/BxiOxsQiv9A7hsTz7DzMw61icdKQAQEbdJ+gxQkb9NRNydUV1mZlYCBYWCpF8AfwUsA7YlzQE4FMzMupCCQgGoBoYnQzxmZtZFFXqfQgPwl1kWYmZmpVfokUJ/4GVJi4EtLY0RcWYmVZmZWUkUGgrXZ1mEmZl1DoVeffR01oWYmVnpFXr10Z/5eI6iXkBP4IOI+IusCjMzs+Ir9EjhoJblZPqKyeSekWBmZl3IHs+Smjzv4CFgYgb1mJlZCRU6fHR23tt9yN23sDmTiszMrGQKvfrof+YtNwOryQ0hmZlZF1LoOQXPWGpm1g0U+pCdcknzJW1IXvMklWddnJmZFVehJ5p/Tu4hOEckr39L2szMrAspNBTKIuLnEdGcvGYDfhammVkXU2gobJJ0kaQeyesiYFOWhZmZWfEVGgpTyT028y1gPXAO8HcZ1WRmZiVS6CWpNwC1EfEugKS+wC3kwsLMzLqIQo8URrYEAkBEvAOMzqYkMzMrlUJDYR9Jh7a8SY4UCj3KMDOzvUShofAD4DlJ35X0XeA/gH9pawNJdyb3NDTktV0vaZ2kZclrUt66b0paJek1SZ5XycysBAq9o/luSXXA+KTp7Ih4+RM2mw38BLh7p/YfRcQt+Q2ShgPnA1Xk7oN4QtJfR8S2QuozM7OOUfAQUBICnxQE+f1/K6miwO6TgTkRsQX4T0mrgBrguUI/z8zM2m+Pp87uAJdLWp4ML7WcpxgIrM3r05i0mZlZERX7ZPFM4LvknuL2XXLnKvboslZJ04BpAIMHD+7o+sw6jbHX7Dzy2n3V/+uXSl1Ct1HUI4WIeDsitkXEduBn5IaIANYBg/K6lidtre1jVkRUR0R1WZln2jAz60hFDQVJA/LengW0XJm0ADhfUm9JlcBQYHExazMzswyHjyTdB4wD+ktqBK4DxkkaRW74aDVwCUBErJD0ALkT2c3AZb7yyMys+DILhYi4oJXmO9rofxNwU1b1mJnZJyvF1UdmZtZJORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCyVWShIulPSBkkNeW19JT0uaWXy89CkXZJulbRK0nJJY7Kqy8zMdi/LI4XZwGk7tX0DWBgRQ4GFyXuA04GhyWsaMDPDuszMbDcyC4WI+C3wzk7Nk4G7kuW7gCl57XdHzvPAIZIGZFWbmZm1rtjnFA6PiPXJ8lvA4cnyQGBtXr/GpM3MzIqoZCeaIyKA2NPtJE2TVCepbuPGjRlUZmbWfRU7FN5uGRZKfm5I2tcBg/L6lSdtu4iIWRFRHRHVZWVlmRZrZtbdFDsUFgC1yXIt8HBe+5eSq5BOAJryhpnMzKxI9s1qx5LuA8YB/SU1AtcB3wcekHQxsAY4N+n+KDAJWAV8CHw5q7rMzGz3MguFiLhgN6smtNI3gMuyqsXMzArjO5rNzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs1Rm01zY3ufNG0aUuoROY/B3Xip1CWYl4SMFMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCxVkmkuJK0G/gxsA5ojolpSX+B+oAJYDZwbEe+Woj4zs+6qlEcKn42IURFRnbz/BrAwIoYCC5P3ZmZWRJ1p+GgycFeyfBcwpYS1mJl1S6UKhQB+I6le0rSk7fCIWJ8svwUcXprSzMy6r1JNnf3fImKdpMOAxyW9mr8yIkJStLZhEiLTAAYPHpx9pWZm3UhJjhQiYl3ycwMwH6gB3pY0ACD5uWE3286KiOqIqC4rKytWyWZm3ULRQ0HSAZIOalkGTgUagAVAbdKtFni42LWZmXV3pRg+OhyYL6nl838ZEY9JWgI8IOliYA1wbglqMzPr1ooeChHxBvA3rbRvAiYUux4zM/tYZ7ok1czMSsyhYGZmKYeCmZmlSnWfgplZwd68YUSpS+g0Bn/npUz37yMFMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzlUDAzs5RDwczMUg4FMzNLORTMzCzV6UJB0mmSXpO0StI3Sl2PmVl30qlCQVIPYAZwOjAcuEDS8NJWZWbWfXSqUABqgFUR8UZE/BcwB5hc4prMzLqNzhYKA4G1ee8bkzYzMyuCfUtdwJ6SNA2Ylrx9X9JrpaynKxkC/YE/lrqOTuE6lboCy+M/m3k65s/mkN2t6GyhsA4YlPe+PGlLRcQsYFYxi+ouJNVFRHWp6zDbmf9sFk9nGz5aAgyVVCmpF3A+sKDENZmZdRud6kghIpolXQ78O9ADuDMiVpS4LDOzbqNThQJARDwKPFrqOropD8tZZ+U/m0WiiCh1DWZm1kl0tnMKZmZWQg6Fbk45z0g6Pa/tbyU9Vsq6zAAkhaQf5L2/WtL1JSypy3ModHORGz+8FPihpD6SDgT+GbistJWZAbAFOFtS/1IX0l04FIyIaAD+DfhH4DvA3RHxemmrMgOgmdxJ5q+VupDuotNdfWQl80/Ai8B/Ab5JyDqTGcBySf9S6kK6A4eCARARH0i6H3g/IraUuh6zFhHxJ0l3A1cCH5W6nq7Ow0eWb3vyMuts/i9wMXBAqQvp6hwKZtbpRcQ7wAPkgsEy5FAws73FD8jNlmoZ8h3NZmaW8pGCmZmlHApmZpZyKJiZWcqhYGZmKYeCmZmlHApmZpZyKFiXJ+n9In/ePpJuldQg6SVJSyRVJuuuLXAfBfUz62i+T8G6PEnvR8SBRfy8C4D/BZwbEdsllQMfRMS7hdZS7JrNWvhIwbolSaMkPS9puaT5kg5N2r+a/M/+95LmSdo/aZ+d/O//PyS9IemcNnY/AFgfEdsBIqIxCYTvA/tJWibp3mS/D0mql7RC0rSkbYd+kiokNeTVnj5oRtKVkl5OvsecDH5V1s34SMG6vNb+1y1pOXBFRDwt6QbgLyLiKkn9ImJT0udG4O2IuE3SbHKTsZ0HDAMWRMRRu/m8cuAZ4D1gIXBPRCxtrRZJfSPiHUn7AUuAkyNiU34/SRXAIxFxbPL+auDAiLhe0v8DKiNii6RDIuK9DvmlWbflIwXrdiQdDBwSEU8nTXcB/yNZPlbS7yS9BFwIVOVt+lBEbI+Il4HDd7f/iGgEjga+SW7W2YWSJuym+5WSfg88DwwChu7h11kO3CvpInIPpDFrF4eC2Y5mA5dHxAhyDx7qk7cu/zkTamsnEbElIn4dEdeQe7zplJ37SBoHfA44MSL+Bli60+e1aGbHv6v5fc4g9xCaMcASSX5GirWLQ8G6nYhoAt6V9N+Tpi8CLUcNBwHrJfUkd6SwxySNkXREsrwPMBJYk6zemuwb4GDg3Yj4UNIw4IS83eT3exs4TFI/Sb2Bz+fte1BEPEXuUaoHAz45be3i/1VYd7C/pMa89z8EaoHbkxPJbwBfTtZNB14ANiY/D/oUn3cY8LPkH3CAxcBPkuVZ5B4t+SIwFbhU0ivAa+SGkNi5X0RcmJz3WAysA15N+vQA7kmGwwTc6nMK1l4+0WxmZikPH5mZWcrDR2afkqQRwC92at4SEceXoh6zjuDhIzMzS3n4yMzMUg4FMzNLORTMzCzlUDAzs5RDwczMUv8f9LS2dzQY9pYAAAAASUVORK5CYII=\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"bRiR2D7qJM17"},"source":["Male are having more chance of getting loan than Female"]},{"cell_type":"code","metadata":{"id":"ZvKm4clnGRam","executionInfo":{"status":"ok","timestamp":1602850046497,"user_tz":-330,"elapsed":1842,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"8e85a286-55d2-4845-bd11-38b8fd3eb456","colab":{"base_uri":"https://localhost:8080/","height":350}},"source":["sns.countplot(data['Loan_Status'],hue=data['Married'])"],"execution_count":116,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n","  FutureWarning\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7fe8fcebd5c0>"]},"metadata":{"tags":[]},"execution_count":116},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAYUAAAEHCAYAAABBW1qbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAV+UlEQVR4nO3dfZBV9Z3n8fcXIWIQjWiHKK1CZhmVIKOko8FZswpmGVkj0VEj8YGgGZwqlbBRs5GUkbWWrWTjw0ac9alQxGFEIpJodE0cYzRWTATUaRGG6CpqG6JIFCMGteG7f/Th5IINdtN9+zb0+1V1657zO0/fSzX96fM7v3NPZCaSJAH0qnUBkqTuw1CQJJUMBUlSyVCQJJUMBUlSqXetC+iIffbZJwcPHlzrMiRph7JkyZI3MrOutWU7dCgMHjyYxYsX17oMSdqhRMRLW1tm95EkqWQoSJJKhoIkqbRDX1OQpM72wQcf0NTUxPr162tdSof17duX+vp6+vTp0+ZtDAVJqtDU1ET//v0ZPHgwEVHrcrZbZrJmzRqampoYMmRIm7ez+0iSKqxfv5699957hw4EgIhg7733bvcZj6EgSVvY0QNhk+35HIaCJKlkKEhSO0QEZ555Zjnf3NxMXV0dJ5xwQof2+/vf/55TTjmlXdt87Wtf46677urQcbfkhWaVXr7i0FqX0G0c8N1nal2Cuql+/fqxdOlS/vznP7Pbbrvx4IMPMmjQoHbto7m5md69e282v99++3X6L/jt4ZmCJLXTuHHjuO+++wC44447mDBhQrnsiSeeYNSoURx++OEcddRRrFixAoDZs2dz4oknMnr0aMaMGfOh+ZUrVzJ8+HAANmzYwCWXXMLnPvc5RowYwY033gi0jCi64IILOOiggzjuuON4/fXXO/2zGQqS1E6nn3468+bNY/369TQ2NnLkkUeWyw4++GB+9atf8dRTT3HFFVcwbdq0ctmTTz7JXXfdxSOPPNLq/CazZs1izz33ZNGiRSxatIibb76ZF198kYULF7JixQqWLVvGnDlz+PWvf93pn83uI0lqpxEjRrBy5UruuOMOxo0bt9mytWvXMnHiRJ577jkigg8++KBc9sUvfpEBAwZsdX6Tn//85zQ2NpbdSWvXruW5557j0UcfZcKECeyyyy7st99+jB49utM/m6EgSdvhxBNP5OKLL+aXv/wla9asKdsvu+wyjj32WBYuXMjKlSs55phjymX9+vXbbB9bzm+SmcycOZOxY8du1n7//fd33gfYCruPJGk7nHPOOVx++eUceujmAzTWrl1bXniePXv2du177NixXH/99eVZxu9+9zvWrVvHF77wBe688042bNjAqlWrePjhhzv0GVpjKEjSdqivr2fKlCkfav/Wt77FpZdeyuGHH05zc/N27fvrX/86w4YNY+TIkQwfPpzzzjuP5uZmTjrpJIYOHcqwYcM4++yzGTVqVEc/xodEZnb6TrtKQ0ND+pCdzuOQ1L9wSGrPtXz5cg455JBal9FpWvs8EbEkMxtaW98zBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJW8o1mStuGzl8zp1P0t+cHZH7lORPDNb36Tq666CoArr7ySd955h+nTp3dqLa3xTEGSupldd92Vu+++mzfeeKPLj20oSFI307t3byZPnsw111zzoWUrV65k9OjRjBgxgjFjxvDyyy936rENBUnqhs4//3zmzp3L2rVrN2u/8MILmThxIo2NjZxxxhmtftVGRxgKktQN7bHHHpx99tlce+21m7U//vjjfPWrXwXgrLPO4rHHHuvU4xoKktRNTZ06lVmzZrFu3bouO6ahIEnd1IABAzjttNOYNWtW2XbUUUcxb948AObOncvRRx/dqcd0SKokbUNbhpBW00UXXcR1111Xzs+cOZNJkybxgx/8gLq6Om699dZOPV7VQiEi9gfmAAOBBG7KzB9GxHTgH4DVxarTMvP+YptLgXOBDcCUzPxZteqTpO7qnXfeKacHDhzIu+++W84feOCB/OIXv6jasat5ptAMXJSZT0ZEf2BJRDxYLLsmM6+sXDkihgGnA58B9gP+NSL+OjM3VLFGSVKFql1TyMxVmflkMf0nYDkwaBubjAfmZeZ7mfki8DxwRLXqkyR9WJdcaI6IwcDhwG+LpgsiojEibomIvYq2QcArFZs10UqIRMTkiFgcEYtXr1695WJJUgdUPRQiYndgATA1M98Grgf+CjgMWAVc1Z79ZeZNmdmQmQ11dXWdXq8k9WRVDYWI6ENLIMzNzLsBMvO1zNyQmRuBm/lLF9GrwP4Vm9cXbZKkLlK1UIiIAGYByzPz6or2fStWOwlYWkzfA5weEbtGxBBgKPBEteqTJH1YNUcf/S1wFvBMRDxdtE0DJkTEYbQMU10JnAeQmc9GxHxgGS0jl8535JGkWnv5ikM7dX8HfPeZbS7PTI4++mi+853vcPzxxwPwox/9iFmzZvHAAw90ai2tqVooZOZjQLSy6P5tbDMDmFGtmiSpu4sIbrjhBk499VSOPfZYmpubmTZtWpcEAnhHsyR1O8OHD+dLX/oS3//+91m3bh1nnnkmM2bMYOnSpXzwwQdMnz6d8ePH8+yzzzJp0iTef/99Nm7cyIIFCxg6dGiHjm0oSFI3dPnllzNy5Eg+9rGPccIJJzB69GhuueUW3nrrLY444giOO+44brjhBr7xjW9wxhln8P7777NhQ8d73A0FSeqG+vXrx1e+8hV233135s+fz7333suVV7Z8EcT69et5+eWXGTVqFDNmzKCpqYmTTz65w2cJYChIUrfVq1cvevXqRWayYMECDjrooM2WH3LIIRx55JHcd999jBs3jhtvvJHRo0d37Jgd2lqSVHVjx45l5syZZCYATz31FAAvvPACn/70p5kyZQrjx4+nsbGxw8fyTEGStuGjhpB2hcsuu4ypU6cyYsQINm7cyJAhQ/jpT3/K/Pnzuf322+nTpw+f+tSnmDZtWoePFZuSZ0fU0NCQixcvrnUZO43OHo+9I+sOvwhUG8uXL+eQQw6pdRmdprXPExFLMrOhtfXtPpIklQwFSVLJUJCkLezI3eqVtudzGAqSVKFv376sWbNmhw+GzGTNmjX07du3Xds5+kiSKtTX19PU1MTO8BCvvn37Ul9f365tDAVJqtCnTx+GDBlS6zJqxu4jSVLJUJAklQwFSVLJUJAklQwFSVLJUJAklQwFSVLJUJAklQwFSVLJUJAklQwFSVLJUJAklQwFSVLJUJAklaoWChGxf0Q8HBHLIuLZiPhG0T4gIh6MiOeK972K9oiIayPi+YhojIiR1apNktS6ap4pNAMXZeYw4PPA+RExDPg28FBmDgUeKuYBjgeGFq/JwPVVrE2S1IqqhUJmrsrMJ4vpPwHLgUHAeOC2YrXbgC8X0+OBOdniN8AnImLfatUnSfqwLrmmEBGDgcOB3wIDM3NVsegPwMBiehDwSsVmTUWbJKmLVD0UImJ3YAEwNTPfrlyWLU/GbtfTsSNickQsjojFO8MzVCWpO6lqKEREH1oCYW5m3l00v7apW6h4f71ofxXYv2Lz+qJtM5l5U2Y2ZGZDXV1d9YqXpB6omqOPApgFLM/MqysW3QNMLKYnAj+paD+7GIX0eWBtRTeTJKkL9K7ivv8WOAt4JiKeLtqmAd8D5kfEucBLwGnFsvuBccDzwLvApCrWJklqRdVCITMfA2Iri8e0sn4C51erHknSR/OOZklSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJXaFAoR8VBb2iRJO7be21oYEX2BjwP7RMReQBSL9gAGVbk2SVIX22YoAOcBU4H9gCX8JRTeBq6rYl2SpBrYZihk5g+BH0bEhZk5s4tqkiTVyEedKQCQmTMj4ihgcOU2mTmnSnVJkmqgTaEQEbcDfwU8DWwomhMwFCRpJ9KmUAAagGGZmdUsRpJUW229T2Ep8KlqFiJJqr22hsI+wLKI+FlE3LPpta0NIuKWiHg9IpZWtE2PiFcj4uniNa5i2aUR8XxErIiIsdv3cSRJHdHW7qPp27Hv2bQMW93yusM1mXllZUNEDANOBz5Dy/DXf42Iv87MDUiSukxbRx890t4dZ+ajETG4jauPB+Zl5nvAixHxPHAE8Hh7jytJ2n5t/ZqLP0XE28VrfURsiIi3t/OYF0REY9G9tFfRNgh4pWKdJrZyx3RETI6IxRGxePXq1dtZgiSpNW0Khczsn5l7ZOYewG7A3wP/ZzuOdz0tQ1sPA1YBV7V3B5l5U2Y2ZGZDXV3ddpQgSdqadn9Larb4MdDui8GZ+VpmbsjMjcDNtHQRAbwK7F+xan3RJknqQm29ee3kitletNy3sL69B4uIfTNzVTF7Ei1DXQHuAf4lIq6m5ULzUOCJ9u5fktQxbR199KWK6WZgJS0Xh7cqIu4AjqHlG1abgMuBYyLiMFruhl5JyxfukZnPRsR8YFmx//MdeSRJXa+to48mtXfHmTmhleZZ21h/BjCjvceRJHWeto4+qo+IhcXNaK9HxIKIqK92cZKkrtXWC8230tLvv1/xurdokyTtRNoaCnWZeWtmNhev2YDjQSVpJ9PWUFgTEWdGxC7F60xgTTULkyR1vbaGwjnAacAfaLnp7BTga1WqSZJUI20dknoFMDEz3wSIiAHAlbSEhSRpJ9HWUBixKRAAMvOPEXF4lWrqUp+9xIfHbbKwf60rkFRrbe0+6lXx5XWbzhTaGiiSpB1EW3+xXwU8HhE/KuZPxRvNJGmn09Y7mudExGJgdNF0cmYuq15ZkqRaaHMXUBECBoEk7cTa/dXZkqSdl6EgSSoZCpKkkqEgSSoZCpKkkqEgSSoZCpKkkqEgSSoZCpKkkqEgSSr5TaeSur2Xrzi01iV0Gwd895mq7t8zBUlSyVCQJJUMBUlSyVCQJJUMBUlSqWqhEBG3RMTrEbG0om1ARDwYEc8V73sV7RER10bE8xHRGBEjq1WXJGnrqnmmMBv4uy3avg08lJlDgYeKeYDjgaHFazJwfRXrkiRtRdVCITMfBf64RfN44LZi+jbgyxXtc7LFb4BPRMS+1apNktS6rr6mMDAzVxXTfwAGFtODgFcq1msq2j4kIiZHxOKIWLx69erqVSpJPVDNLjRnZgK5HdvdlJkNmdlQV1dXhcokqefq6lB4bVO3UPH+etH+KrB/xXr1RZskqQt1dSjcA0wspicCP6loP7sYhfR5YG1FN5MkqYtU7QvxIuIO4Bhgn4hoAi4HvgfMj4hzgZeA04rV7wfGAc8D7wKTqlWXJGnrqhYKmTlhK4vGtLJuAudXqxZJUtt4R7MkqWQoSJJKhoIkqWQoSJJKhoIkqWQoSJJKhoIkqWQoSJJKhoIkqVS1O5oldcxnL5lT6xK6jYX9a11Bz+GZgiSpZChIkkqGgiSpZChIkkqGgiSpZChIkkqGgiSpZChIkkqGgiSpZChIkkqGgiSpZChIkkqGgiSpZChIkkqGgiSpZChIkkqGgiSpVJMnr0XESuBPwAagOTMbImIAcCcwGFgJnJaZb9aiPknqqWp5pnBsZh6WmQ3F/LeBhzJzKPBQMS9J6kLdqftoPHBbMX0b8OUa1iJJPVKtQiGBn0fEkoiYXLQNzMxVxfQfgIG1KU2Seq6aXFMA/mNmvhoRnwQejIh/r1yYmRkR2dqGRYhMBjjggAOqX6kk9SA1OVPIzFeL99eBhcARwGsRsS9A8f76Vra9KTMbMrOhrq6uq0qWpB6hy0MhIvpFRP9N08B/BpYC9wATi9UmAj/p6tokqaerRffRQGBhRGw6/r9k5gMRsQiYHxHnAi8Bp9WgNknq0bo8FDLzBeBvWmlfA4zp6nokSX/RnYakSpJqzFCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJW6XShExN9FxIqIeD4ivl3reiSpJ+lWoRARuwD/BBwPDAMmRMSw2lYlST1HtwoF4Ajg+cx8ITPfB+YB42tckyT1GL1rXcAWBgGvVMw3AUdWrhARk4HJxew7EbGii2rb6R0I+wBv1LqObuHyqHUFquDPZoXO+dk8cGsLulsofKTMvAm4qdZ17IwiYnFmNtS6DmlL/mx2ne7WffQqsH/FfH3RJknqAt0tFBYBQyNiSER8DDgduKfGNUlSj9Gtuo8yszkiLgB+BuwC3JKZz9a4rJ7Ebjl1V/5sdpHIzFrXIEnqJrpb95EkqYYMBUlSyVDo4aLFYxFxfEXbqRHxQC3rkgAiIiPiqor5iyNieg1L2ukZCj1ctlxU+kfg6ojoGxG7A/8TOL+2lUkAvAecHBH71LqQnsJQEJm5FLgX+G/Ad4E5mfn/aluVBEAzLSOP/mutC+kputWQVNXUfweeBN4HvHNU3ck/AY0R8b9qXUhPYCgIgMxcFxF3Au9k5nu1rkfaJDPfjog5wBTgz7WuZ2dn95EqbSxeUnfzv4FzgX61LmRnZyhI6vYy84/AfFqCQVVkKEjaUVxFy1doq4r8mgtJUskzBUlSyVCQJJUMBUlSyVCQJJUMBUlSyVCQJJUMBe30IuKdLj5er4i4NiKWRsQzEbEoIoYUy6a1cR9tWk/qbN6noJ1eRLyTmbt34fEmAH8PnJaZGyOiHliXmW+2tZaurlnaxDMF9UgRcVhE/CYiGiNiYUTsVbT/Q/GX/b9FxIKI+HjRPrv46//XEfFCRJyyjd3vC6zKzI0AmdlUBML3gN0i4umImFvs98cRsSQino2IyUXbZutFxOCIWFpRe/mgmYiYEhHLis8xrwr/VOphPFPQTq+1v7ojohG4MDMfiYgrgD0yc2pE7J2Za4p1/gfwWmbOjIjZtHwZ21eAg4F7MvM/bOV49cBjwFvAQ8A/Z+ZTrdUSEQMy848RsRuwCPhPmbmmcr2IGAz8NDOHF/MXA7tn5vSI+D0wJDPfi4hPZOZbnfKPph7LMwX1OBGxJ/CJzHykaLoN+EIxPTwifhURzwBnAJ+p2PTHmbkxM5cBA7e2/8xsAg4CLqXlW2cfiogxW1l9SkT8G/AbYH9gaDs/TiMwNyLOpOWBNFKHGArS5mYDF2TmobQ8eKhvxbLK50zEtnaSme9l5v/NzEtoebzpl7dcJyKOAY4DRmXm3wBPbXG8TZrZ/P9q5Tr/hZaH0IwEFkWEz0hRhxgK6nEycy3wZkQcXTSdBWw6a+gPrIqIPrScKbRbRIyMiP2K6V7ACOClYvEHxb4B9gTezMx3I+Jg4PMVu6lc7zXgkxGxd0TsCpxQse/9M/NhWh6luifgxWl1iH9VqCf4eEQ0VcxfDUwEbiguJL8ATCqWXQb8FlhdvPffjuN9Eri5+AUO8ARwXTF9Ey2PlnwSOAf4x4hYDqygpQuJLdfLzDOK6x5PAK8C/16sswvwz0V3WADXek1BHeWFZklSye4jSVLJ7iNpO0XEocDtWzS/l5lH1qIeqTPYfSRJKtl9JEkqGQqSpJKhIEkqGQqSpNL/B0Y/KVuSoPHHAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"8BQVAEH6IzQZ"},"source":["Married People will get more chance of loan than non married people"]},{"cell_type":"code","metadata":{"id":"jkMmE_gWGacY","executionInfo":{"status":"ok","timestamp":1602850047283,"user_tz":-330,"elapsed":2202,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"25127c69-7763-463f-b938-459dc5f743c1","colab":{"base_uri":"https://localhost:8080/","height":350}},"source":["sns.countplot(data['Loan_Status'],hue=data['Dependents'])"],"execution_count":117,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n","  FutureWarning\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7fe8fcd73160>"]},"metadata":{"tags":[]},"execution_count":117},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"Le_ur5pgJZFD"},"source":["As Dependent Count decreases chances of getting loan increases"]},{"cell_type":"code","metadata":{"id":"OmpE75XQJiSe","executionInfo":{"status":"ok","timestamp":1602850047284,"user_tz":-330,"elapsed":1750,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"238a874b-5407-476e-9079-2fa725be3294","colab":{"base_uri":"https://localhost:8080/","height":350}},"source":["sns.countplot(data['Loan_Status'],hue=data['Education'])"],"execution_count":118,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n","  FutureWarning\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7fe8fcce3780>"]},"metadata":{"tags":[]},"execution_count":118},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAYUAAAEHCAYAAABBW1qbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAd7ElEQVR4nO3deXRV5fn28e9NGGIFZQoUgRqWL4iGQAxBKIpQqGMVRGUSBbRLSgWcCnXqa6nKbyliqUMXissasLSoKAiu1rf+GCoUqCQxhMGiqLGGIgYQCgpI4H7/ODvbQwgkQM45Ibk+a52VvZ/97L3vhOHKnp5t7o6IiAhAnUQXICIi1YdCQUREQgoFEREJKRRERCSkUBARkVDdRBdwMpo3b+6pqamJLkNE5JSSm5u7zd1TylsWs1Aws2TgXaBBsJ+57v5rM8sGegO7gq6j3D3fzAx4CrgK+CZozzvWPlJTU8nJyYnVtyAiUiOZ2WdHWxbLI4X9QF9332Nm9YDlZvbXYNlEd59bpv+VQPvg0x2YHnwVEZE4idk1BY/YE8zWCz7HelJuADArWG8V0NjMWsWqPhEROVJMLzSbWZKZ5QNfAu+4+z+DRZPNrMDMpplZg6CtNfB51OpFQZuIiMRJTC80u/tBIMPMGgPzzKwTcD/wBVAfmAHcCzxc2W2a2WhgNMAPfvCDKq9ZRI7fgQMHKCoqYt++fYkuRaIkJyfTpk0b6tWrV+l14nL3kbvvNLMlwBXuPjVo3m9mLwETgvnNQNuo1doEbWW3NYNImJCVlaWBm0SqgaKiIho1akRqaiqRe0Yk0dyd7du3U1RURLt27Sq9XsxOH5lZSnCEgJmdBlwK/Kv0OkFwt9G1wLpglQXACIvoAexy9y2xqk9Eqs6+ffto1qyZAqEaMTOaNWt23EdvsTxSaAXMNLMkIuHzqru/ZWaLzSwFMCAfGBP0/wuR21E3Ebkl9ZYY1iYiVUyBUP2cyJ9JzELB3QuAC8pp73uU/g6MjVU9IiJSMQ1zISKnlKSkJDIyMsLPY489dkSfpUuXcvXVV1fpfpcuXcqKFSvC+eeee45Zs2ZV6T6qg1N6mIuq0HVizftDPVG5T4xIdAkiFTrttNPIz8+P+36XLl1Kw4YN6dmzJwBjxoypYI1Tk44URKRGePvtt+nYsSOZmZm88cYbYfukSZOYOnVqON+pUycKCwsBmDVrFp07d6ZLly7cfPPNACxcuJDu3btzwQUX8OMf/5itW7dSWFjIc889x7Rp08jIyGDZsmWHbTc/P58ePXrQuXNnBg4cyFdffQVAnz59uPfee7nwwgvp0KEDy5Yti9NP48QpFETklLJ3797DTh+98sor7Nu3j9tuu42FCxeSm5vLF198UeF21q9fz6OPPsrixYtZs2YNTz31FAAXX3wxq1at4v3332fo0KFMmTKF1NRUxowZw913301+fj69evU6bFsjRozg8ccfp6CggPT0dH7zm9+Ey0pKSnjvvff43e9+d1h7dVXrTx+JyKmlvNNH+fn5tGvXjvbt2wNw0003MWPGjGNuZ/HixQwaNIjmzZsD0LRpUyDyzMWQIUPYsmUL3377bYX3+O/atYudO3fSu3dvAEaOHMmgQYPC5ddddx0AXbt2DY9QqjMdKYhIjVa3bl0OHToUzld03/748eMZN24ca9eu5fnnnz/pp7QbNIiM5JOUlERJSclJbSseFAoicsrr2LEjhYWFfPzxxwD8+c9/DpelpqaSlxcZhT8vL49PP/0UgL59+/Laa6+xfft2AHbs2AFEfvNv3Toy7NrMmTPD7TRq1Ijdu3cfse8zzzyTJk2ahNcLXn755fCo4VSkUBCRU0rZawr33XcfycnJzJgxg5/85CdkZmbSokWLsP/111/Pjh07SEtL49lnn6VDhw4ApKWl8eCDD9K7d2+6dOnCPffcA0QuTA8aNIiuXbuGp5YArrnmGubNmxdeaI42c+ZMJk6cSOfOncnPz+ehhx6Kw08iNizyzNipKSsry0/2JTu6JfU7uiVVTtQHH3zAeeedl+gypBzl/dmYWa67Z5XXX0cKIiISUiiIiEhIoSAiIiGFgoiIhBQKIiISUiiIiEhIw1yISJWr6lu9K3O79NatW7n77rtZtWoVTZo0oX79+vzyl79k4MCBJ7TPSZMm0bBhQyZMmFBx5zIKCwtZsWIFN9544wntO5F0pCAipzx359prr+WSSy7hk08+ITc3lzlz5lBUVHRYv3gNM1FYWMif/vSnuOyrqikUROSUt3jxYurXr3/YOw7OPvtsxo8fT3Z2Nv3796dv377069ePPXv20K9fPzIzM0lPT+fNN98M15k8eTIdOnTg4osvZuPGjWF7nz59KH1Qdtu2baSmpgKR//x79epFZmYmmZmZ4Ut47rvvPpYtW0ZGRgbTpk3j4MGDTJw4kW7dutG5c2eef/75OPxUToxOH4nIKW/9+vVkZmYedXleXh4FBQU0bdqUkpIS5s2bxxlnnMG2bdvo0aMH/fv3Jy8vjzlz5pCfn09JSQmZmZl07dr1mPtt0aIF77zzDsnJyXz00UcMGzaMnJwcHnvsMaZOncpbb70FwIwZMzjzzDNZvXo1+/fv56KLLuKyyy6rcATWRFAoiEiNM3bsWJYvX079+vUZO3Ysl156aTg0trvzwAMP8O6771KnTh02b97M1q1bWbZsGQMHDuR73/seAP37969wPwcOHGDcuHHk5+eTlJTEhx9+WG6/v/3tbxQUFDB37lwgMujeRx99pFAQEYmFtLQ0Xn/99XD+97//Pdu2bSMrKzK8z+mnnx4umz17NsXFxeTm5lKvXj1SU1MrHB47evjt6L7Tpk2jZcuWrFmzhkOHDpGcnFzu+u7OM888w+WXX37C32O86JqCiJzy+vbty759+5g+fXrY9s0335Tbd9euXbRo0YJ69eqxZMkSPvvsMwAuueQS5s+fz969e9m9ezcLFy4M10lNTSU3Nxcg/G2/dFutWrWiTp06vPzyyxw8eBA4cpjtyy+/nOnTp3PgwAEAPvzwQ77++usq+u6rVsyOFMwsGXgXaBDsZ667/9rM2gFzgGZALnCzu39rZg2AWUBXYDswxN0LY1WfiMROvEfcNTPmz5/P3XffzZQpU0hJSeH000/n8ccfZ+/evYf1HT58ONdccw3p6elkZWXRsWNHADIzMxkyZAhdunShRYsWdOvWLVxnwoQJDB48OByeu9Ttt9/O9ddfz6xZs7jiiivCI5LOnTuTlJREly5dGDVqFHfeeSeFhYVkZmbi7qSkpDB//vw4/GSOX8yGzjYzA0539z1mVg9YDtwJ3AO84e5zzOw5YI27Tzez24HO7j7GzIYCA919yLH2oaGzq5aGzpYTpaGzq69qM3S2R+wJZusFHwf6AqXHXzOBa4PpAcE8wfJ+QbCIiEicxPSagpklmVk+8CXwDvAxsNPdS58gKQJaB9Otgc8BguW7iJxiKrvN0WaWY2Y5xcXFsSxfRKTWiWkouPtBd88A2gAXAh2rYJsz3D3L3bNSUlJOukYREflOXO4+cvedwBLgh0BjMyu9wN0G2BxMbwbaAgTLzyRywVlEROIkZqFgZilm1jiYPg24FPiASDjcEHQbCZQ+Y74gmCdYvthP5RdIi4icgmL58ForYKaZJREJn1fd/S0z2wDMMbNHgfeBF4P+LwIvm9kmYAcwNIa1iYhIOWIWCu5eAFxQTvsnRK4vlG3fBwyKVT0iEj//fji9Srf3g4fWVtjHzLjnnnt48sknAZg6dSp79uxh0qRJR11n/vz5dOjQgfPPP7/c5X/84x+ZMmUKBw8epG7dunTr1o2pU6fSuHHjE/o+ABo2bMiePXsq7liO7OxsLrvsMs4666wT3n9F9ESziNQIDRo04I033mDbtm2VXmf+/Pls2LCh3GVvv/0206ZN469//Svr168nLy+Pnj17snXr1iP6lj7JHGvZ2dn85z//iek+FAoiUiPUrVuX0aNHM23atCOWFRYW0rdvXzp37ky/fv3497//zYoVK1iwYAETJ04kIyODjz/++LB1Jk+ezNSpU2ndOnLXfFJSErfeeivnnnsuEBn64t577yUzM5PXXnuNF154gW7dutGlSxeuv/76cJiNTz/9lB/+8Iekp6fzq1/9Ktz+0qVLufrqq8P5cePGkZ2dDcDDDz9Mt27d6NSpE6NHj8bdmTt3Ljk5OQwfPpyMjAz27t1Lbm4uvXv3pmvXrlx++eVs2bLlpH+OCgURqTHGjh3L7Nmz2bVr12Ht48ePZ+TIkRQUFDB8+HDuuOMOevbsSf/+/XniiSfIz8/nnHPOOWydiobjBmjWrBl5eXkMHTqU6667jtWrV7NmzRrOO+88Xnwxcrn0zjvv5Oc//zlr166lVatWlfo+xo0bx+rVq1m3bh179+7lrbfe4oYbbiArK4vZs2eTn59P3bp1GT9+PHPnziU3N5dbb72VBx988Dh+WuVTKIhIjXHGGWcwYsQInn766cPaV65cGb4a8+abb2b58uXHtd21a9eSkZHBOeecwyuvvBK2Dxny3Ug869ato1evXqSnpzN79mzWr18PwD/+8Q+GDRsW7rsylixZQvfu3UlPT2fx4sXhtqJt3LiRdevWcemll5KRkcGjjz56xJvmToSGzhaRGuWuu+4iMzOTW2655aS2k5aWRl5eHj/60Y9IT08nPz+fcePGHTbAXvSQ3KNGjWL+/Pl06dKF7Oxsli5dGi4rb8Se6OG44bshufft28ftt99OTk4Obdu2ZdKkSeUO7e3upKWlsXLlypP6PsvSkYKI1ChNmzZl8ODB4ekbgJ49ezJnzhwg8j6FXr16AUcOcR3t/vvvZ8KECYf99l12xNVou3fvplWrVhw4cIDZs2eH7RdddNFh+y519tlns2HDBvbv38/OnTtZtGgR8F04NG/enD179hw2VHd0veeeey7FxcVhKBw4cKDcI4rjpSMFEalylbmFNJZ+8Ytf8Oyzz4bzzzzzDLfccgtPPPEEKSkpvPTSSwAMHTqU2267jaeffpq5c+cedl3hqquuori4mCuvvJKDBw/SuHFjOnXqdNQX5TzyyCN0796dlJQUunfvHv7n/dRTT3HjjTfy+OOPM2DAgLB/27ZtGTx4MJ06daJdu3ZccEHkDv7GjRtz22230alTJ77//e8fNoT3qFGjGDNmDKeddhorV65k7ty53HHHHezatYuSkhLuuusu0tLSTupnF7Ohs+NBQ2dXLQ2dLSdKQ2dXX9Vm6GwRETn1KBRERCSkUBCRKnEqn4quqU7kz0ShICInLTk5me3btysYqhF3Z/v27SQnJx/Xerr7SEROWps2bSgqKkJvQ6xekpOTadOmzXGto1AQkZNWr1492rVrl+gypAro9JGIiIQUCiIiElIoiIhISKEgIiIhhYKIiIQUCiIiElIoiIhIKGahYGZtzWyJmW0ws/VmdmfQPsnMNptZfvC5Kmqd+81sk5ltNLPyx6cVEZGYieXDayXAL9w9z8waAblm9k6wbJq7T43ubGbnA0OBNOAs4H/NrIO7H4xhjSIiEiVmRwruvsXd84Lp3cAHQOtjrDIAmOPu+939U2ATcGGs6hMRkSPF5ZqCmaUCFwD/DJrGmVmBmf3BzJoEba2Bz6NWK+LYISIiIlUs5qFgZg2B14G73P2/wHTgHCAD2AI8eZzbG21mOWaWo8G3RESqVkxDwczqEQmE2e7+BoC7b3X3g+5+CHiB704RbQbaRq3eJmg7jLvPcPcsd89KSUmJZfkiIrVOLO8+MuBF4AN3/21Ue6uobgOBdcH0AmComTUws3ZAe+C9WNUnIiJHiuXdRxcBNwNrzSw/aHsAGGZmGYADhcDPANx9vZm9CmwgcufSWN15JCISXzELBXdfDlg5i/5yjHUmA5NjVZOIiBybnmgWEZGQQkFEREIKBRERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUREQkpFAQEZGQQkFEREIxCwUza2tmS8xsg5mtN7M7g/amZvaOmX0UfG0StJuZPW1mm8yswMwyY1WbiIiUL5ZHCiXAL9z9fKAHMNbMzgfuAxa5e3tgUTAPcCXQPviMBqbHsDYRESlHzELB3be4e14wvRv4AGgNDABmBt1mAtcG0wOAWR6xCmhsZq1iVZ+IiBwpLtcUzCwVuAD4J9DS3bcEi74AWgbTrYHPo1YrCtrKbmu0meWYWU5xcXHMahYRqY1iHgpm1hB4HbjL3f8bvczdHfDj2Z67z3D3LHfPSklJqcJKRUSkUqFgZosq01ZOn3pEAmG2u78RNG8tPS0UfP0yaN8MtI1avU3QJiIicXLMUDCzZDNrCjQ3sybBnUNNg9NBR5zaKbOuAS8CH7j7b6MWLQBGBtMjgTej2kcEdyH1AHZFnWYSEZE4qFvB8p8BdwFnAbmABe3/BZ6tYN2LgJuBtWaWH7Q9ADwGvGpmPwU+AwYHy/4CXAVsAr4Bbqn8tyEiIlXhmKHg7k8BT5nZeHd/5ng27O7L+S5EyupXTn8Hxh7PPkREpGpVdKQAgLs/Y2Y9gdToddx9VozqEhGRBKhUKJjZy8A5QD5wMGh2QKEgIlKDVCoUgCzg/OAUj4iI1FCVfU5hHfD9WBYiIiKJV9kjhebABjN7D9hf2uju/WNSlYiIJERlQ2FSLIsQEZHqobJ3H/091oWIiEjiVfbuo918N0ZRfaAe8LW7nxGrwkREJP4qe6TQqHQ6GL5iAJF3JIiISA1y3KOkBu87mA9cHoN6REQkgSp7+ui6qNk6RJ5b2BeTikREJGEqe/fRNVHTJUAhkVNIIiJSg1T2moJGLBURqQUq+5KdNmY2z8y+DD6vm1mbWBcnIiLxVdkLzS8ReQnOWcFnYdAmIiI1SGVDIcXdX3L3kuCTDegFySIiNUxlQ2G7md1kZknB5yZgeywLExGR+KtsKNxK5LWZXwBbgBuAUTGqSUREEqSyt6Q+DIx0968AzKwpMJVIWIiISA1R2SOFzqWBAODuO4ALYlOSiIgkSmVDoY6ZNSmdCY4UKnuUISIip4jKhsKTwEoze8TMHgFWAFOOtYKZ/SF4pmFdVNskM9tsZvnB56qoZfeb2SYz22hmGldJRCQBKvtE8ywzywH6Bk3XufuGClbLBp4FZpVpn+buU6MbzOx8YCiQRuQ5iP81sw7ufrAy9YmISNWo9CmgIAQqCoLo/u+aWWoluw8A5rj7fuBTM9sEXAisrOz+RETk5B330NlVYJyZFQSnl0qvU7QGPo/qUxS0iYhIHMU7FKYD5wAZRJ53ePJ4N2Bmo80sx8xyiouLq7o+EZFaLa6h4O5b3f2gux8CXiByighgM9A2qmuboK28bcxw9yx3z0pJ0UgbIiJVKa6hYGatomYHAqV3Ji0AhppZAzNrB7QH3otnbSIiEsNnDczsz0AfoLmZFQG/BvqYWQbgRF7U8zMAd19vZq8SuZBdAozVnUciIvEXs1Bw92HlNL94jP6TgcmxqkdERCqWiLuPRESkmtJQFSLVVNeJZZ/7rL1ynxiR6BJqDR0piIhISKEgIiIhhYKIiIQUCiIiElIoiIhISKEgIiIhhYKIiIQUCiIiElIoiIhISKEgIiIhhYKIiIQUCiIiElIoiIhISKEgIiIhhYKIiIQUCiIiElIoiIhISKEgIiIhhYKIiIQUCiIiEopZKJjZH8zsSzNbF9XW1MzeMbOPgq9NgnYzs6fNbJOZFZhZZqzqEhGRo4vlkUI2cEWZtvuARe7eHlgUzANcCbQPPqOB6TGsS0REjiJmoeDu7wI7yjQPAGYG0zOBa6PaZ3nEKqCxmbWKVW0iIlK+eF9TaOnuW4LpL4CWwXRr4POofkVB2xHMbLSZ5ZhZTnFxcewqFRGphRJ2odndHfATWG+Gu2e5e1ZKSkoMKhMRqb3iHQpbS08LBV+/DNo3A22j+rUJ2kREJI7iHQoLgJHB9Ejgzaj2EcFdSD2AXVGnmUREJE7qxmrDZvZnoA/Q3MyKgF8DjwGvmtlPgc+AwUH3vwBXAZuAb4BbYlWXiIgcXcxCwd2HHWVRv3L6OjA2VrWIiEjl6IlmEREJKRRERCSkUBARkZBCQUREQgoFEREJxezuIzn1/Pvh9ESXUG384KG1iS5BJCF0pCAiIiGFgoiIhBQKIiISUiiIiEhIoSAiIiGFgoiIhBQKIiISUiiIiEhIoSAiIiGFgoiIhBQKIiISUiiIiEhIoSAiIiGFgoiIhBQKIiISSsj7FMysENgNHARK3D3LzJoCrwCpQCEw2N2/SkR9IiK1VSKPFH7k7hnunhXM3wcscvf2wKJgXkRE4qg6vXltANAnmJ4JLAXuTVQxIlJ96K2A34n1WwETdaTgwN/MLNfMRgdtLd19SzD9BdCyvBXNbLSZ5ZhZTnFxcTxqFRGpNRJ1pHCxu282sxbAO2b2r+iF7u5m5uWt6O4zgBkAWVlZ5fYREZETk5AjBXffHHz9EpgHXAhsNbNWAMHXLxNRm4hIbRb3UDCz082sUek0cBmwDlgAjAy6jQTejHdtIiK1XSJOH7UE5plZ6f7/5O5vm9lq4FUz+ynwGTA4AbWJiNRqcQ8Fd/8E6FJO+3agX7zrERGR7+iJZhERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUREQkVO1CwcyuMLONZrbJzO5LdD0iIrVJtQoFM0sCfg9cCZwPDDOz8xNblYhI7VGtQgG4ENjk7p+4+7fAHGBAgmsSEak16ia6gDJaA59HzRcB3aM7mNloYHQwu8fMNsapthrvbGgObEt0HdXCry3RFUgU/d2MUjV/N88+2oLqFgoVcvcZwIxE11ETmVmOu2clug6RsvR3M36q2+mjzUDbqPk2QZuIiMRBdQuF1UB7M2tnZvWBocCCBNckIlJrVKvTR+5eYmbjgP8HJAF/cPf1CS6rNtFpOamu9HczTszdE12DiIhUE9Xt9JGIiCSQQkFEREIKhVrOIpab2ZVRbYPM7O1E1iUCYGZuZk9GzU8ws0kJLKnGUyjUch65qDQG+K2ZJZtZQ+B/gLGJrUwEgP3AdWbWPNGF1BYKBcHd1wELgXuBh4BZ7v5xYqsSAaCEyJ1Hdye6kNqiWt2SKgn1GyAP+BbQk6NSnfweKDCzKYkupDZQKAgA7v61mb0C7HH3/YmuR6SUu//XzGYBdwB7E11PTafTRxLtUPARqW5+B/wUOD3RhdR0CgURqfbcfQfwKpFgkBhSKIjIqeJJIkNoSwxpmAsREQnpSEFEREIKBRERCSkUREQkpFAQEZGQQkFEREIKBRERCSkUpMYzsz1x3l8dM3vazNaZ2VozW21m7YJlD1RyG5XqJ1LV9JyC1HhmtsfdG8Zxf8OA64HB7n7IzNoAX7v7V5WtJd41i5TSkYLUSmaWYWarzKzAzOaZWZOg/bbgN/s1Zva6mX0vaM8OfvtfYWafmNkNx9h8K2CLux8CcPeiIBAeA04zs3wzmx1sd76Z5ZrZejMbHbQd1s/MUs1sXVTt4YtmzOwOM9sQfB9zYvCjklpGRwpS45X3W7eZFQDj3f3vZvYwcIa732Vmzdx9e9DnUWCruz9jZtlEBmMbAnQEFrj7/znK/toAy4GdwCLgj+7+fnm1mFlTd99hZqcBq4He7r49up+ZpQJvuXunYH4C0NDdJ5nZf4B27r7fzBq7+84q+aFJraUjBal1zOxMoLG7/z1omglcEkx3MrNlZrYWGA6kRa06390PufsGoOXRtu/uRcC5wP1ERp1dZGb9jtL9DjNbA6wC2gLtj/PbKQBmm9lNRF5II3JSFAoih8sGxrl7OpEXDyVHLYt+z4QdayPuvt/d/+ruE4m83vTasn3MrA/wY+CH7t4FeL/M/kqVcPi/1eg+PyHyEppMYLWZ6R0pclIUClLruPsu4Csz6xU03QyUHjU0AraYWT0iRwrHzcwyzeysYLoO0Bn4LFh8INg2wJnAV+7+jZl1BHpEbSa631aghZk1M7MGwNVR227r7kuIvEr1TEAXp+Wk6LcKqQ2+Z2ZFUfO/BUYCzwUXkj8BbgmW/V/gn0Bx8LXRCeyvBfBC8B84wHvAs8H0DCKvlswDbgXGmNkHwEYip5Ao28/dhwfXPd4DNgP/CvokAX8MTocZ8LSuKcjJ0oVmEREJ6fSRiIiEdPpI5ASZWTrwcpnm/e7ePRH1iFQFnT4SEZGQTh+JiEhIoSAiIiGFgoiIhBQKIiIS+v8SAkEuC/5IlAAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"pcr0FVgQJmgL"},"source":["Person who is educated will have a more chance of getting the loan than the non graduate"]},{"cell_type":"code","metadata":{"id":"WedZJWSirGWZ","executionInfo":{"status":"ok","timestamp":1602850047285,"user_tz":-330,"elapsed":1271,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"573dcfd3-dd64-40a3-d186-784272768a6f","colab":{"base_uri":"https://localhost:8080/","height":350}},"source":["sns.countplot(data['Loan_Status'],hue=data['Self_Employed'])"],"execution_count":119,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n","  FutureWarning\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7fe8fccbd588>"]},"metadata":{"tags":[]},"execution_count":119},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"MNIM0Nb-KE0t","executionInfo":{"status":"ok","timestamp":1602850048048,"user_tz":-330,"elapsed":1790,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"5083a6cb-20a9-4378-8865-cdd23299a953","colab":{"base_uri":"https://localhost:8080/","height":297}},"source":["sns.boxplot(x='Loan_Status',y='ApplicantIncome',data=data)"],"execution_count":120,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"yXKMD2sXKova","executionInfo":{"status":"ok","timestamp":1602850048736,"user_tz":-330,"elapsed":2259,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"e2ec1b4e-8dde-4b18-ed66-f193f55f2243","colab":{"base_uri":"https://localhost:8080/","height":458}},"source":["sns.jointplot(x='Loan_Status',y='ApplicantIncome',data=data)"],"execution_count":121,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<seaborn.axisgrid.JointGrid at 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\n","text/plain":["<Figure size 432x432 with 3 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"vCsRA7WBLMBD"},"source":["If a person is having more income then he has some chance of getting loan but we are not so confident as these may be outliers"]},{"cell_type":"code","metadata":{"id":"REB2Xy5DK5dP","executionInfo":{"status":"ok","timestamp":1602850048737,"user_tz":-330,"elapsed":1754,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"9826f7e9-3792-49d5-b1b9-0e81ebf6c7bd","colab":{"base_uri":"https://localhost:8080/","height":386}},"source":["sns.displot(data['ApplicantIncome'])"],"execution_count":122,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<seaborn.axisgrid.FacetGrid at 0x7fe8fcd78898>"]},"metadata":{"tags":[]},"execution_count":122},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 360x360 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"B3sDCf2kL7WF"},"source":["Mostly applicant's income is between 0K-15K"]},{"cell_type":"code","metadata":{"id":"PCx6KXQYMD-y","executionInfo":{"status":"ok","timestamp":1602850050537,"user_tz":-330,"elapsed":2978,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"fbc6b710-e0ed-41e0-b374-4e16a895de74","colab":{"base_uri":"https://localhost:8080/","height":458}},"source":["sns.jointplot(x='LoanAmount',y='ApplicantIncome',data=data)"],"execution_count":123,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<seaborn.axisgrid.JointGrid at 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\n","text/plain":["<Figure size 432x432 with 3 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"MLQqIpWrIH_1","executionInfo":{"status":"ok","timestamp":1602850050538,"user_tz":-330,"elapsed":2740,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"0da360e6-5026-415c-f48c-0488f4f7a75f","colab":{"base_uri":"https://localhost:8080/","height":373}},"source":["corr=data.corr()\n","sns.heatmap(corr)"],"execution_count":124,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"1jD7ZyLKIXky","executionInfo":{"status":"ok","timestamp":1602850050540,"user_tz":-330,"elapsed":1989,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data.drop(['LoanAmount'],axis=1,inplace=True)"],"execution_count":125,"outputs":[]},{"cell_type":"code","metadata":{"id":"gP5mnZasIn4J","executionInfo":{"status":"ok","timestamp":1602850050541,"user_tz":-330,"elapsed":1406,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"91c15e02-0675-4038-ed46-1d9bde3daa8a","colab":{"base_uri":"https://localhost:8080/","height":350}},"source":["sns.countplot(data['Loan_Status'],hue=data['Credit_History'])"],"execution_count":126,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n","  FutureWarning\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7fe8fc4650f0>"]},"metadata":{"tags":[]},"execution_count":126},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"OtqMep23F2sS"},"source":["## Handling Missing Values"]},{"cell_type":"code","metadata":{"id":"--6Pom4TNqxb","executionInfo":{"status":"ok","timestamp":1602850051055,"user_tz":-330,"elapsed":1507,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["loan_credit_1Y=data['Loan_Status']=='Y'"],"execution_count":127,"outputs":[]},{"cell_type":"code","metadata":{"id":"TUbnHYmGPDEO","executionInfo":{"status":"ok","timestamp":1602850051056,"user_tz":-330,"elapsed":1288,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["loan_credit_1Y=list(loan_credit_1Y)"],"execution_count":128,"outputs":[]},{"cell_type":"code","metadata":{"id":"_TevNztSHcBT","executionInfo":{"status":"ok","timestamp":1602850051056,"user_tz":-330,"elapsed":1070,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data.loc[loan_credit_1Y,'Credit_History']=data.loc[loan_credit_1Y,'Credit_History'].fillna(1.0)"],"execution_count":129,"outputs":[]},{"cell_type":"code","metadata":{"id":"ENOzqIFlO0CQ","executionInfo":{"status":"ok","timestamp":1602850051509,"user_tz":-330,"elapsed":1291,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"647cde4e-25a6-428b-ac6e-9298a1254fd5","colab":{"base_uri":"https://localhost:8080/","height":218}},"source":["data.isnull().sum()"],"execution_count":130,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Gender               13\n","Married               3\n","Dependents           15\n","Education             0\n","Self_Employed        32\n","ApplicantIncome       0\n","CoapplicantIncome     0\n","Loan_Amount_Term     14\n","Credit_History       13\n","Property_Area         0\n","Loan_Status           0\n","dtype: int64"]},"metadata":{"tags":[]},"execution_count":130}]},{"cell_type":"code","metadata":{"id":"q2ImjTWEPmbn","executionInfo":{"status":"ok","timestamp":1602850051510,"user_tz":-330,"elapsed":1060,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["loan_credit_0N=data['Loan_Status']=='N'"],"execution_count":131,"outputs":[]},{"cell_type":"code","metadata":{"id":"mE5cyGkEqxPT","executionInfo":{"status":"ok","timestamp":1602850052203,"user_tz":-330,"elapsed":1531,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["loan_credit_0N=list(loan_credit_0N)"],"execution_count":132,"outputs":[]},{"cell_type":"code","metadata":{"id":"3ODea_Pbq0i2","executionInfo":{"status":"ok","timestamp":1602850052204,"user_tz":-330,"elapsed":1324,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data.loc[loan_credit_0N,'Credit_History']=data.loc[loan_credit_0N,'Credit_History'].fillna(0.0)"],"execution_count":133,"outputs":[]},{"cell_type":"code","metadata":{"id":"jRNcN0xxq7kY","executionInfo":{"status":"ok","timestamp":1602850052204,"user_tz":-330,"elapsed":1072,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"ebe0341b-a9b5-4e22-977b-bdc533dc11a6","colab":{"base_uri":"https://localhost:8080/","height":218}},"source":["data.isnull().sum()"],"execution_count":134,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Gender               13\n","Married               3\n","Dependents           15\n","Education             0\n","Self_Employed        32\n","ApplicantIncome       0\n","CoapplicantIncome     0\n","Loan_Amount_Term     14\n","Credit_History        0\n","Property_Area         0\n","Loan_Status           0\n","dtype: int64"]},"metadata":{"tags":[]},"execution_count":134}]},{"cell_type":"code","metadata":{"id":"KjiBKGaHq9hB","executionInfo":{"status":"ok","timestamp":1602850052726,"user_tz":-330,"elapsed":1360,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"d564a748-b046-4fde-e1b7-d89fda059ef2","colab":{"base_uri":"https://localhost:8080/","height":438}},"source":["data.dropna()"],"execution_count":135,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Gender</th>\n","      <th>Married</th>\n","      <th>Dependents</th>\n","      <th>Education</th>\n","      <th>Self_Employed</th>\n","      <th>ApplicantIncome</th>\n","      <th>CoapplicantIncome</th>\n","      <th>Loan_Amount_Term</th>\n","      <th>Credit_History</th>\n","      <th>Property_Area</th>\n","      <th>Loan_Status</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>Male</td>\n","      <td>No</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>5849</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Male</td>\n","      <td>Yes</td>\n","      <td>1</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>4583</td>\n","      <td>1508.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Rural</td>\n","      <td>N</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Male</td>\n","      <td>Yes</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>Yes</td>\n","      <td>3000</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Male</td>\n","      <td>Yes</td>\n","      <td>0</td>\n","      <td>Not Graduate</td>\n","      <td>No</td>\n","      <td>2583</td>\n","      <td>2358.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Male</td>\n","      <td>No</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>6000</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>609</th>\n","      <td>Female</td>\n","      <td>No</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>2900</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Rural</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>610</th>\n","      <td>Male</td>\n","      <td>Yes</td>\n","      <td>3+</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>4106</td>\n","      <td>0.0</td>\n","      <td>180.0</td>\n","      <td>1.0</td>\n","      <td>Rural</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>611</th>\n","      <td>Male</td>\n","      <td>Yes</td>\n","      <td>1</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>8072</td>\n","      <td>240.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>612</th>\n","      <td>Male</td>\n","      <td>Yes</td>\n","      <td>2</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>7583</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>613</th>\n","      <td>Female</td>\n","      <td>No</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>Yes</td>\n","      <td>4583</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>0.0</td>\n","      <td>Semiurban</td>\n","      <td>N</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>542 rows × 11 columns</p>\n","</div>"],"text/plain":["     Gender Married Dependents  ... Credit_History Property_Area  Loan_Status\n","0      Male      No          0  ...            1.0         Urban            Y\n","1      Male     Yes          1  ...            1.0         Rural            N\n","2      Male     Yes          0  ...            1.0         Urban            Y\n","3      Male     Yes          0  ...            1.0         Urban            Y\n","4      Male      No          0  ...            1.0         Urban            Y\n","..      ...     ...        ...  ...            ...           ...          ...\n","609  Female      No          0  ...            1.0         Rural            Y\n","610    Male     Yes         3+  ...            1.0         Rural            Y\n","611    Male     Yes          1  ...            1.0         Urban            Y\n","612    Male     Yes          2  ...            1.0         Urban            Y\n","613  Female      No          0  ...            0.0     Semiurban            N\n","\n","[542 rows x 11 columns]"]},"metadata":{"tags":[]},"execution_count":135}]},{"cell_type":"code","metadata":{"id":"ZBI4Z7P0vGEc","executionInfo":{"status":"ok","timestamp":1602850052727,"user_tz":-330,"elapsed":1134,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data.dropna(inplace=True,axis=0)"],"execution_count":136,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"nScOIoC602DD"},"source":["# Data Encoding"]},{"cell_type":"code","metadata":{"id":"oQbq4J-l00T2","executionInfo":{"status":"ok","timestamp":1602850053847,"user_tz":-330,"elapsed":1278,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["from sklearn.preprocessing import LabelEncoder"],"execution_count":137,"outputs":[]},{"cell_type":"code","metadata":{"id":"QePxoPO31XHK","executionInfo":{"status":"ok","timestamp":1602850054521,"user_tz":-330,"elapsed":1424,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["le=LabelEncoder()"],"execution_count":138,"outputs":[]},{"cell_type":"code","metadata":{"id":"p04zMk7W1Zgc","executionInfo":{"status":"ok","timestamp":1602850055045,"user_tz":-330,"elapsed":1275,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"e73e099e-7df6-47f7-a45e-7d2362db21cc","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["le.fit(data['Gender'])"],"execution_count":139,"outputs":[{"output_type":"execute_result","data":{"text/plain":["LabelEncoder()"]},"metadata":{"tags":[]},"execution_count":139}]},{"cell_type":"code","metadata":{"id":"3F0xQaIo1eu8","executionInfo":{"status":"ok","timestamp":1602850055526,"user_tz":-330,"elapsed":1557,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"ca5bb214-edfd-4a89-fc9d-f680ce81f5f7","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["le.classes_"],"execution_count":140,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array(['Female', 'Male'], dtype=object)"]},"metadata":{"tags":[]},"execution_count":140}]},{"cell_type":"code","metadata":{"id":"u2PxKmqi1iMs","executionInfo":{"status":"ok","timestamp":1602850055526,"user_tz":-330,"elapsed":1314,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data['Gender']=le.transform(data['Gender'])"],"execution_count":141,"outputs":[]},{"cell_type":"code","metadata":{"id":"DUILshbm1ucb","executionInfo":{"status":"ok","timestamp":1602850055527,"user_tz":-330,"elapsed":1080,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"d6803541-015a-419f-a372-905c890769da","colab":{"base_uri":"https://localhost:8080/","height":232}},"source":["data.head()"],"execution_count":142,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Gender</th>\n","      <th>Married</th>\n","      <th>Dependents</th>\n","      <th>Education</th>\n","      <th>Self_Employed</th>\n","      <th>ApplicantIncome</th>\n","      <th>CoapplicantIncome</th>\n","      <th>Loan_Amount_Term</th>\n","      <th>Credit_History</th>\n","      <th>Property_Area</th>\n","      <th>Loan_Status</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>No</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>5849</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>Yes</td>\n","      <td>1</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>4583</td>\n","      <td>1508.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Rural</td>\n","      <td>N</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>Yes</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>Yes</td>\n","      <td>3000</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>Yes</td>\n","      <td>0</td>\n","      <td>Not Graduate</td>\n","      <td>No</td>\n","      <td>2583</td>\n","      <td>2358.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>No</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>6000</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Gender Married Dependents  ... Credit_History Property_Area  Loan_Status\n","0       1      No          0  ...            1.0         Urban            Y\n","1       1     Yes          1  ...            1.0         Rural            N\n","2       1     Yes          0  ...            1.0         Urban            Y\n","3       1     Yes          0  ...            1.0         Urban            Y\n","4       1      No          0  ...            1.0         Urban            Y\n","\n","[5 rows x 11 columns]"]},"metadata":{"tags":[]},"execution_count":142}]},{"cell_type":"code","metadata":{"id":"YGUcGvSX1xuk","executionInfo":{"status":"ok","timestamp":1602850055929,"user_tz":-330,"elapsed":1243,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"c86c753a-0c52-4199-90c7-f82341193b90","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["le.fit(data['Married'])"],"execution_count":143,"outputs":[{"output_type":"execute_result","data":{"text/plain":["LabelEncoder()"]},"metadata":{"tags":[]},"execution_count":143}]},{"cell_type":"code","metadata":{"id":"eZ5DS59t13pb","executionInfo":{"status":"ok","timestamp":1602850055929,"user_tz":-330,"elapsed":994,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"277d22c8-b244-4461-9ffc-6635348e6f74","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["le.classes_"],"execution_count":144,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array(['No', 'Yes'], dtype=object)"]},"metadata":{"tags":[]},"execution_count":144}]},{"cell_type":"code","metadata":{"id":"7U4pNCnL150y","executionInfo":{"status":"ok","timestamp":1602850056420,"user_tz":-330,"elapsed":1097,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data['Married']=le.transform(data['Married'])"],"execution_count":145,"outputs":[]},{"cell_type":"code","metadata":{"id":"RpFfgBSM2Ap1","executionInfo":{"status":"ok","timestamp":1602850057019,"user_tz":-330,"elapsed":1314,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"f6f3ee75-9a0b-4beb-95ad-495200569009","colab":{"base_uri":"https://localhost:8080/","height":232}},"source":["data.head()"],"execution_count":146,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Gender</th>\n","      <th>Married</th>\n","      <th>Dependents</th>\n","      <th>Education</th>\n","      <th>Self_Employed</th>\n","      <th>ApplicantIncome</th>\n","      <th>CoapplicantIncome</th>\n","      <th>Loan_Amount_Term</th>\n","      <th>Credit_History</th>\n","      <th>Property_Area</th>\n","      <th>Loan_Status</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>5849</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>Graduate</td>\n","      <td>No</td>\n","      <td>4583</td>\n","      <td>1508.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Rural</td>\n","      <td>N</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>Graduate</td>\n","      <td>Yes</td>\n","      <td>3000</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","   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Credit_History Property_Area  Loan_Status\n","0       1        0          0  ...            1.0         Urban            Y\n","1       1        1          1  ...            1.0         Rural            N\n","2       1        1          0  ...            1.0         Urban            Y\n","3       1        1          0  ...            1.0         Urban            Y\n","4       1        0          0  ...            1.0         Urban            Y\n","\n","[5 rows x 11 columns]"]},"metadata":{"tags":[]},"execution_count":146}]},{"cell_type":"code","metadata":{"id":"pDEwYxqR3oQi","executionInfo":{"status":"ok","timestamp":1602850057020,"user_tz":-330,"elapsed":979,"user":{"displayName":"Kota sai durga 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Credit_History Property_Area  Loan_Status\n","0       1        0           0  ...             1.0         Urban            Y\n","1       1        1           1  ...             1.0         Rural            N\n","2       1        1           0  ...             1.0         Urban            Y\n","3       1        1           0  ...             1.0         Urban            Y\n","4       1        0           0  ...             1.0         Urban            Y\n","\n","[5 rows x 11 columns]"]},"metadata":{"tags":[]},"execution_count":153}]},{"cell_type":"code","metadata":{"id":"9vqLqyG_4MAX","executionInfo":{"status":"ok","timestamp":1602850059552,"user_tz":-330,"elapsed":941,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data['Self_Employed']=le.fit_transform(data['Self_Employed'])"],"execution_count":154,"outputs":[]},{"cell_type":"code","metadata":{"id":"ypdydo5V4Q8J","executionInfo":{"status":"ok","timestamp":1602850059946,"user_tz":-330,"elapsed":987,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"1a3f68d9-cef8-41b9-a9a7-cb169308c0c0","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["le.classes_"],"execution_count":155,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array(['No', 'Yes'], dtype=object)"]},"metadata":{"tags":[]},"execution_count":155}]},{"cell_type":"code","metadata":{"id":"Pau2ChL84S4G","executionInfo":{"status":"ok","timestamp":1602850060436,"user_tz":-330,"elapsed":1103,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"b332df4f-1365-4be5-9d08-5078806d73c6","colab":{"base_uri":"https://localhost:8080/","height":215}},"source":["data.head()"],"execution_count":156,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Gender</th>\n","      <th>Married</th>\n","      <th>Dependents</th>\n","      <th>Education</th>\n","      <th>Self_Employed</th>\n","      <th>ApplicantIncome</th>\n","      <th>CoapplicantIncome</th>\n","      <th>Loan_Amount_Term</th>\n","      <th>Credit_History</th>\n","      <th>Property_Area</th>\n","      <th>Loan_Status</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>5849</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>4583</td>\n","      <td>1508.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Rural</td>\n","      <td>N</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>3000</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>2583</td>\n","      <td>2358.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>6000</td>\n","      <td>0.0</td>\n","      <td>360.0</td>\n","      <td>1.0</td>\n","      <td>Urban</td>\n","      <td>Y</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Gender  Married  Dependents  ...  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kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"985a8a26-ebbf-44a5-d5f2-f6d070c359bd","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["le.fit(data['Credit_History'])"],"execution_count":163,"outputs":[{"output_type":"execute_result","data":{"text/plain":["LabelEncoder()"]},"metadata":{"tags":[]},"execution_count":163}]},{"cell_type":"code","metadata":{"id":"IKYlk0dn5NZm","executionInfo":{"status":"ok","timestamp":1602850063409,"user_tz":-330,"elapsed":1113,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"b2a54889-17fa-4085-cd55-4a16965f5c23","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["le.classes_"],"execution_count":164,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([0., 1.])"]},"metadata":{"tags":[]},"execution_count":164}]},{"cell_type":"code","metadata":{"id":"o6ToPP015QT5","executionInfo":{"status":"ok","timestamp":1602850063409,"user_tz":-330,"elapsed":902,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data['Credit_History']=le.transform(data['Credit_History'])"],"execution_count":165,"outputs":[]},{"cell_type":"code","metadata":{"id":"-798uHsnTxR0","executionInfo":{"status":"ok","timestamp":1602850097638,"user_tz":-330,"elapsed":1190,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data['Loan_Amount_Term']=le.fit_transform(data['Loan_Amount_Term'])"],"execution_count":166,"outputs":[]},{"cell_type":"code","metadata":{"id":"GqqdTWXbT7BJ","executionInfo":{"status":"ok","timestamp":1602850111955,"user_tz":-330,"elapsed":1035,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"c6217458-2a37-4598-a6d6-9f8c41f70c66","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["le.classes_"],"execution_count":167,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([ 12.,  36.,  60.,  84., 120., 180., 240., 300., 360., 480.])"]},"metadata":{"tags":[]},"execution_count":167}]},{"cell_type":"code","metadata":{"id":"FQhDq5jHT9XV","executionInfo":{"status":"ok","timestamp":1602850124266,"user_tz":-330,"elapsed":1225,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"8df7375e-a236-4c0d-b7ee-f850834f8b78","colab":{"base_uri":"https://localhost:8080/","height":215}},"source":["data.head()"],"execution_count":168,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Gender</th>\n","      <th>Married</th>\n","      <th>Dependents</th>\n","      <th>Education</th>\n","      <th>Self_Employed</th>\n","      <th>ApplicantIncome</th>\n","      <th>CoapplicantIncome</th>\n","      <th>Loan_Amount_Term</th>\n","      <th>Credit_History</th>\n","      <th>Property_Area</th>\n","      <th>Loan_Status</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>5849</td>\n","      <td>0.0</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>4583</td>\n","      <td>1508.0</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>3000</td>\n","      <td>0.0</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>2583</td>\n","      <td>2358.0</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>6000</td>\n","      <td>0.0</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Gender  Married  Dependents  ...  Credit_History  Property_Area  Loan_Status\n","0       1        0           0  ...               1              2            1\n","1       1        1           1  ...               1              0            0\n","2       1        1           0  ...               1              2            1\n","3       1        1           0  ...               1              2            1\n","4       1        0           0  ...               1              2            1\n","\n","[5 rows x 11 columns]"]},"metadata":{"tags":[]},"execution_count":168}]},{"cell_type":"markdown","metadata":{"id":"uouOrcffUErS"},"source":["# MinMax Scaling"]},{"cell_type":"code","metadata":{"id":"pVc73Sv8UKgT","executionInfo":{"status":"ok","timestamp":1602850191049,"user_tz":-330,"elapsed":991,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["from sklearn.preprocessing import MinMaxScaler"],"execution_count":169,"outputs":[]},{"cell_type":"code","metadata":{"id":"0jtMDMH5UQGL","executionInfo":{"status":"ok","timestamp":1602850201246,"user_tz":-330,"elapsed":991,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["mms=MinMaxScaler()"],"execution_count":170,"outputs":[]},{"cell_type":"code","metadata":{"id":"ul0VewGIUSoD","executionInfo":{"status":"ok","timestamp":1602850278380,"user_tz":-330,"elapsed":1952,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data['ApplicantIncome']=mms.fit_transform(np.array(data['ApplicantIncome']).reshape(-1,1))"],"execution_count":172,"outputs":[]},{"cell_type":"code","metadata":{"id":"wuk9_IWGUl_y","executionInfo":{"status":"ok","timestamp":1602850297358,"user_tz":-330,"elapsed":1068,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"c6d78f85-4cb3-4f64-83c1-4640f718b4e4","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["mms.data_range_"],"execution_count":173,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([80850.])"]},"metadata":{"tags":[]},"execution_count":173}]},{"cell_type":"code","metadata":{"id":"3vyAEHZXUqWo","executionInfo":{"status":"ok","timestamp":1602850307523,"user_tz":-330,"elapsed":1691,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"bcded3cb-90fd-4532-86f5-ddc16335aabc","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["mms.data_min_"],"execution_count":174,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([150.])"]},"metadata":{"tags":[]},"execution_count":174}]},{"cell_type":"code","metadata":{"id":"agmF2W6BUsfl","executionInfo":{"status":"ok","timestamp":1602850319914,"user_tz":-330,"elapsed":1185,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"9817b3b0-0f17-4838-c8a7-ed517c708d4a","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["mms.data_max_"],"execution_count":175,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([81000.])"]},"metadata":{"tags":[]},"execution_count":175}]},{"cell_type":"code","metadata":{"id":"FMeSJia4UysF","executionInfo":{"status":"ok","timestamp":1602850370090,"user_tz":-330,"elapsed":1106,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["mmsc=MinMaxScaler()"],"execution_count":176,"outputs":[]},{"cell_type":"code","metadata":{"id":"4aiVJkCLU7uJ","executionInfo":{"status":"ok","timestamp":1602850596344,"user_tz":-330,"elapsed":1065,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["data['CoapplicantIncome']=mmsc.fit_transform(np.array(data['CoapplicantIncome']).reshape(-1,1))"],"execution_count":178,"outputs":[]},{"cell_type":"code","metadata":{"id":"d3FmTue-Vzu0","executionInfo":{"status":"ok","timestamp":1602850633114,"user_tz":-330,"elapsed":1045,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"2e6749c0-8f5a-4696-e15a-ed8411257a52","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["mmsc.data_range_"],"execution_count":179,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([33837.])"]},"metadata":{"tags":[]},"execution_count":179}]},{"cell_type":"code","metadata":{"id":"3ktCcVizV8l7","executionInfo":{"status":"ok","timestamp":1602850647732,"user_tz":-330,"elapsed":1453,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"b4502720-fa85-4e54-9b08-6d950e510c4b","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["mmsc.data_min_"],"execution_count":180,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([0.])"]},"metadata":{"tags":[]},"execution_count":180}]},{"cell_type":"code","metadata":{"id":"Fhq14lgoV_sm","executionInfo":{"status":"ok","timestamp":1602850657664,"user_tz":-330,"elapsed":1455,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"be00e22c-1b05-4fb2-ad7f-c21845952f87","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["mmsc.data_max_"],"execution_count":181,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([33837.])"]},"metadata":{"tags":[]},"execution_count":181}]},{"cell_type":"markdown","metadata":{"id":"JJ6cy9mQvN2h"},"source":["# Splitting The Data"]},{"cell_type":"code","metadata":{"id":"lkPOtWXCvLop","executionInfo":{"status":"ok","timestamp":1602850665333,"user_tz":-330,"elapsed":1064,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["from sklearn.model_selection import train_test_split"],"execution_count":182,"outputs":[]},{"cell_type":"code","metadata":{"id":"hT5drHbCvXbf","executionInfo":{"status":"ok","timestamp":1602850668374,"user_tz":-330,"elapsed":1118,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["x_train,x_test,y_train,y_test=train_test_split(data.drop(['Loan_Status'],axis=1),data['Loan_Status'],test_size=0.2,random_state=42)"],"execution_count":183,"outputs":[]},{"cell_type":"code","metadata":{"id":"oanvki-7yLCa","executionInfo":{"status":"ok","timestamp":1602850670672,"user_tz":-330,"elapsed":1227,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"5b4363a3-a25a-45d9-fb41-663bf7bb38b3","colab":{"base_uri":"https://localhost:8080/","height":402}},"source":["x_test"],"execution_count":184,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Gender</th>\n","      <th>Married</th>\n","      <th>Dependents</th>\n","      <th>Education</th>\n","      <th>Self_Employed</th>\n","      <th>ApplicantIncome</th>\n","      <th>CoapplicantIncome</th>\n","      <th>Loan_Amount_Term</th>\n","      <th>Credit_History</th>\n","      <th>Property_Area</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>409</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>3</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1.000000</td>\n","      <td>0.000000</td>\n","      <td>8</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>83</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0.072356</td>\n","      <td>0.066495</td>\n","      <td>8</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>402</th>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0.029066</td>\n","      <td>0.591069</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>97</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0.022597</td>\n","      <td>0.029465</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>270</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0.038182</td>\n","      <td>0.000000</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>2</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>172</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>3</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0.041707</td>\n","      <td>0.000000</td>\n","      <td>5</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>55</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0.031639</td>\n","      <td>0.034489</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>106</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0.139357</td>\n","      <td>0.033277</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>2</td>\n","    </tr>\n","    <tr>\n","      <th>556</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0.031132</td>\n","      <td>0.048024</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>2</td>\n","    </tr>\n","    <tr>\n","      <th>606</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0.040198</td>\n","      <td>0.073884</td>\n","      <td>8</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>109 rows × 10 columns</p>\n","</div>"],"text/plain":["     Gender  Married  ...  Credit_History  Property_Area\n","409       1        1  ...               0              0\n","83        1        1  ...               0              1\n","402       1        0  ...               1              1\n","97        1        1  ...               1              1\n","270       0        0  ...               1              2\n","..      ...      ...  ...             ...            ...\n","172       1        1  ...               1              0\n","55        1        1  ...               1              1\n","106       1        1  ...               1              2\n","556       0        0  ...               1              2\n","606       1        1  ...               1              1\n","\n","[109 rows x 10 columns]"]},"metadata":{"tags":[]},"execution_count":184}]},{"cell_type":"markdown","metadata":{"id":"J2NfysYM0YJs"},"source":["# *Model Preparation*"]},{"cell_type":"markdown","metadata":{"id":"6S4yUvUm0gQ2"},"source":["## Logistic Regression"]},{"cell_type":"code","metadata":{"id":"w6u82hS6yRLM","executionInfo":{"status":"ok","timestamp":1602850681077,"user_tz":-330,"elapsed":1976,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["from sklearn.linear_model import LogisticRegression"],"execution_count":185,"outputs":[]},{"cell_type":"code","metadata":{"id":"8C_G--mX0nDg","executionInfo":{"status":"ok","timestamp":1602850681967,"user_tz":-330,"elapsed":2543,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["model_lg=LogisticRegression()"],"execution_count":186,"outputs":[]},{"cell_type":"code","metadata":{"id":"y_0QNl0C0rII","executionInfo":{"status":"ok","timestamp":1602850681969,"user_tz":-330,"elapsed":2266,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"c5e50098-0be0-48a7-cf0d-2339263467ab","colab":{"base_uri":"https://localhost:8080/","height":101}},"source":["model_lg.fit(x_train,y_train)"],"execution_count":187,"outputs":[{"output_type":"execute_result","data":{"text/plain":["LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n","                   intercept_scaling=1, l1_ratio=None, max_iter=100,\n","                   multi_class='auto', n_jobs=None, penalty='l2',\n","                   random_state=None, solver='lbfgs', tol=0.0001, verbose=0,\n","                   warm_start=False)"]},"metadata":{"tags":[]},"execution_count":187}]},{"cell_type":"code","metadata":{"id":"-E38LxUA0t51","executionInfo":{"status":"ok","timestamp":1602850681971,"user_tz":-330,"elapsed":2081,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["y_pred_lr=model_lg.predict(x_test)"],"execution_count":188,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"jlCa02-f5yiZ"},"source":["## SVM"]},{"cell_type":"code","metadata":{"id":"qr3cOMey5727","executionInfo":{"status":"ok","timestamp":1602850682737,"user_tz":-330,"elapsed":2459,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["from sklearn.svm import SVC"],"execution_count":189,"outputs":[]},{"cell_type":"code","metadata":{"id":"oPRqi_3o572-","executionInfo":{"status":"ok","timestamp":1602850682739,"user_tz":-330,"elapsed":2207,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["model_svm=SVC()"],"execution_count":190,"outputs":[]},{"cell_type":"code","metadata":{"id":"_oCin5Xc573A","executionInfo":{"status":"ok","timestamp":1602850682740,"user_tz":-330,"elapsed":2043,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"5c5219bc-85a7-423a-8f16-6454aca61112","colab":{"base_uri":"https://localhost:8080/","height":84}},"source":["model_svm.fit(x_train,y_train)"],"execution_count":191,"outputs":[{"output_type":"execute_result","data":{"text/plain":["SVC(C=1.0, break_ties=False, cache_size=200, class_weight=None, coef0=0.0,\n","    decision_function_shape='ovr', degree=3, gamma='scale', kernel='rbf',\n","    max_iter=-1, probability=False, random_state=None, shrinking=True,\n","    tol=0.001, verbose=False)"]},"metadata":{"tags":[]},"execution_count":191}]},{"cell_type":"code","metadata":{"id":"uyAdwvwS573D","executionInfo":{"status":"ok","timestamp":1602850682741,"user_tz":-330,"elapsed":1830,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["y_pred_svm=model_svm.predict(x_test)"],"execution_count":192,"outputs":[]},{"cell_type":"code","metadata":{"id":"X1IxLOel5gje","executionInfo":{"status":"ok","timestamp":1602850682742,"user_tz":-330,"elapsed":1695,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":[""],"execution_count":192,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"bjjmhmRa6WA-"},"source":["## Decision Tree"]},{"cell_type":"code","metadata":{"id":"gs-gpSsv6aUl","executionInfo":{"status":"ok","timestamp":1602850684908,"user_tz":-330,"elapsed":3378,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["from sklearn.tree import DecisionTreeClassifier"],"execution_count":193,"outputs":[]},{"cell_type":"code","metadata":{"id":"Shmv95uw6aUv","executionInfo":{"status":"ok","timestamp":1602850684910,"user_tz":-330,"elapsed":3175,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["model_dtc=DecisionTreeClassifier()"],"execution_count":194,"outputs":[]},{"cell_type":"code","metadata":{"id":"8Z7LvFGG6aU0","executionInfo":{"status":"ok","timestamp":1602850684911,"user_tz":-330,"elapsed":2968,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"acae5d8c-8fb3-49ce-a08c-8f5bc9874bc6","colab":{"base_uri":"https://localhost:8080/","height":118}},"source":["model_dtc.fit(x_train,y_train)"],"execution_count":195,"outputs":[{"output_type":"execute_result","data":{"text/plain":["DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n","                       max_depth=None, max_features=None, max_leaf_nodes=None,\n","                       min_impurity_decrease=0.0, min_impurity_split=None,\n","                       min_samples_leaf=1, min_samples_split=2,\n","                       min_weight_fraction_leaf=0.0, presort='deprecated',\n","                       random_state=None, splitter='best')"]},"metadata":{"tags":[]},"execution_count":195}]},{"cell_type":"code","metadata":{"id":"pVhw5rJJ6aU7","executionInfo":{"status":"ok","timestamp":1602850684913,"user_tz":-330,"elapsed":2778,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["y_pred_dtc=model_dtc.predict(x_test)"],"execution_count":196,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"zl9CW3406p5n"},"source":["## RandomForest Classifier"]},{"cell_type":"code","metadata":{"id":"ebk0KdFn6vqB","executionInfo":{"status":"ok","timestamp":1602850684914,"user_tz":-330,"elapsed":2320,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["from sklearn.ensemble import RandomForestClassifier"],"execution_count":197,"outputs":[]},{"cell_type":"code","metadata":{"id":"jwVNvafV6vqM","executionInfo":{"status":"ok","timestamp":1602850684918,"user_tz":-330,"elapsed":2068,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["model_rfc=RandomForestClassifier()"],"execution_count":198,"outputs":[]},{"cell_type":"code","metadata":{"id":"9yzpGShf6vqQ","executionInfo":{"status":"ok","timestamp":1602850684924,"user_tz":-330,"elapsed":1796,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"c0fffaf9-c93e-4a8b-cfe7-b33bffbca047","colab":{"base_uri":"https://localhost:8080/","height":151}},"source":["model_rfc.fit(x_train,y_train)"],"execution_count":199,"outputs":[{"output_type":"execute_result","data":{"text/plain":["RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,\n","                       criterion='gini', max_depth=None, max_features='auto',\n","                       max_leaf_nodes=None, max_samples=None,\n","                       min_impurity_decrease=0.0, min_impurity_split=None,\n","                       min_samples_leaf=1, min_samples_split=2,\n","                       min_weight_fraction_leaf=0.0, n_estimators=100,\n","                       n_jobs=None, oob_score=False, random_state=None,\n","                       verbose=0, warm_start=False)"]},"metadata":{"tags":[]},"execution_count":199}]},{"cell_type":"code","metadata":{"id":"Ybj9ck_96vqU","executionInfo":{"status":"ok","timestamp":1602850684926,"user_tz":-330,"elapsed":1596,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["y_pred_rfc=model_rfc.predict(x_test)"],"execution_count":200,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"LvY4GtR677-9"},"source":["## Naive Bayes MultinomialDB"]},{"cell_type":"code","metadata":{"id":"Vt9-9mba6Zh6","executionInfo":{"status":"ok","timestamp":1602850685426,"user_tz":-330,"elapsed":1571,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["from sklearn.naive_bayes import MultinomialNB"],"execution_count":201,"outputs":[]},{"cell_type":"code","metadata":{"id":"Vb6FXFLH8NJj","executionInfo":{"status":"ok","timestamp":1602850685428,"user_tz":-330,"elapsed":1176,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["model_mnb=MultinomialNB()"],"execution_count":202,"outputs":[]},{"cell_type":"code","metadata":{"id":"vBINRozi8Q4E","executionInfo":{"status":"ok","timestamp":1602850685430,"user_tz":-330,"elapsed":960,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"d9fa651d-d074-4a2f-c99c-2feaaa647058","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["model_mnb.fit(x_train,y_train)"],"execution_count":203,"outputs":[{"output_type":"execute_result","data":{"text/plain":["MultinomialNB(alpha=1.0, class_prior=None, fit_prior=True)"]},"metadata":{"tags":[]},"execution_count":203}]},{"cell_type":"code","metadata":{"id":"FVTokwYl8Y6C","executionInfo":{"status":"ok","timestamp":1602850686713,"user_tz":-330,"elapsed":2076,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["y_pred_mnb=model_mnb.predict(x_test)"],"execution_count":204,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"arK0P4SR9BIi"},"source":["## KNN"]},{"cell_type":"code","metadata":{"id":"NacR2XnM-TOI","executionInfo":{"status":"ok","timestamp":1602850687245,"user_tz":-330,"elapsed":1525,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["from sklearn.neighbors import KNeighborsClassifier"],"execution_count":205,"outputs":[]},{"cell_type":"code","metadata":{"id":"WZyMOEV4-TOO","executionInfo":{"status":"ok","timestamp":1602850707714,"user_tz":-330,"elapsed":989,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["model_knn=KNeighborsClassifier()"],"execution_count":207,"outputs":[]},{"cell_type":"code","metadata":{"id":"rVHFWWcM-TOR","executionInfo":{"status":"ok","timestamp":1602850709242,"user_tz":-330,"elapsed":749,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"922edf5d-2ae8-46da-c499-c170fd3961cc","colab":{"base_uri":"https://localhost:8080/","height":67}},"source":["model_knn.fit(x_train,y_train)"],"execution_count":208,"outputs":[{"output_type":"execute_result","data":{"text/plain":["KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n","                     metric_params=None, n_jobs=None, n_neighbors=5, p=2,\n","                     weights='uniform')"]},"metadata":{"tags":[]},"execution_count":208}]},{"cell_type":"code","metadata":{"id":"Y4DtTUQf-TOU","executionInfo":{"status":"ok","timestamp":1602850710177,"user_tz":-330,"elapsed":1138,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["y_pred_knn=model_knn.predict(x_test)"],"execution_count":209,"outputs":[]},{"cell_type":"code","metadata":{"id":"7JRo9TBS8f04","executionInfo":{"status":"ok","timestamp":1602850717303,"user_tz":-330,"elapsed":962,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"56df9b33-fa7c-49c6-c9da-06786b3e22ad","colab":{"base_uri":"https://localhost:8080/","height":101}},"source":["y_pred"],"execution_count":210,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1,\n","       1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1,\n","       1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1,\n","       1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1,\n","       1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1])"]},"metadata":{"tags":[]},"execution_count":210}]},{"cell_type":"markdown","metadata":{"id":"17SG1cpPW5WL"},"source":["# Metrics Measurement"]},{"cell_type":"code","metadata":{"id":"LKqwKhrnWREX","executionInfo":{"status":"ok","timestamp":1602850939648,"user_tz":-330,"elapsed":1389,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["import sklearn.metrics as m"],"execution_count":212,"outputs":[]},{"cell_type":"code","metadata":{"id":"yA8KtvjEYD5N","executionInfo":{"status":"ok","timestamp":1602851420326,"user_tz":-330,"elapsed":1218,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["y_predict=[]\n","for i in range(len(y_test)):\n","  y_p=[np.array(y_test)[i],y_pred_dtc[i],y_pred_knn[i],y_pred_lr[i],y_pred_mnb[i],y_pred_rfc[i],y_pred_svm[i]]\n","  y_predict.append(y_p)\n"],"execution_count":223,"outputs":[]},{"cell_type":"code","metadata":{"id":"O-rd99yoXaFn","executionInfo":{"status":"ok","timestamp":1602851424963,"user_tz":-330,"elapsed":1263,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["y_predictions_all=pd.DataFrame(y_predict,columns=['y_actual','Decision Tree','KNN','Logistic Regression','Multinomial NB','RandomForestClassifier','SupportVectorMachine'])"],"execution_count":224,"outputs":[]},{"cell_type":"code","metadata":{"id":"FXj3EhnrX6y0","executionInfo":{"status":"ok","timestamp":1602851427938,"user_tz":-330,"elapsed":982,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"f1ae957f-d805-42b2-fcfd-2e8da3578f36","colab":{"base_uri":"https://localhost:8080/","height":402}},"source":["y_predictions_all"],"execution_count":225,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>y_actual</th>\n","      <th>Decision Tree</th>\n","      <th>KNN</th>\n","      <th>Logistic Regression</th>\n","      <th>Multinomial NB</th>\n","      <th>RandomForestClassifier</th>\n","      <th>SupportVectorMachine</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>104</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>105</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>106</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>107</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>108</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>109 rows × 7 columns</p>\n","</div>"],"text/plain":["     y_actual  Decision Tree  ...  RandomForestClassifier  SupportVectorMachine\n","0           0              1  ...                       0                     0\n","1           0              0  ...                       0                     0\n","2           1              1  ...                       1                     1\n","3           1              1  ...                       1                     1\n","4           1              1  ...                       1                     1\n","..        ...            ...  ...                     ...                   ...\n","104         0              0  ...                       1                     1\n","105         1              1  ...                       1                     1\n","106         1              1  ...                       1                     1\n","107         1              1  ...                       1                     1\n","108         1              1  ...                       1                     1\n","\n","[109 rows x 7 columns]"]},"metadata":{"tags":[]},"execution_count":225}]},{"cell_type":"code","metadata":{"id":"MnDR9--5X9To","executionInfo":{"status":"ok","timestamp":1602851637440,"user_tz":-330,"elapsed":1312,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["y_models=[y_pred_dtc,y_pred_knn,y_pred_lr,y_pred_mnb,y_pred_rfc,y_pred_svm]"],"execution_count":226,"outputs":[]},{"cell_type":"code","metadata":{"id":"EkpGE9GwZwMW","executionInfo":{"status":"ok","timestamp":1602852330520,"user_tz":-330,"elapsed":2070,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["metrics=[]\n","for y_pred in y_models:\n","  mt=[m.accuracy_score(y_test,y_pred),m.f1_score(y_test,y_pred),m.log_loss(y_test,y_pred),m.precision_score(y_test,y_pred),m.recall_score(y_test,y_pred)]\n","  metrics.append(mt)"],"execution_count":227,"outputs":[]},{"cell_type":"code","metadata":{"id":"1XbSXIdDcZMw","executionInfo":{"status":"ok","timestamp":1602852369690,"user_tz":-330,"elapsed":1477,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["model_names=['Decision Tree','KNN','Logistic Regression','Multinomial NB','RandomForestClassifier','SupportVectorMachine']"],"execution_count":228,"outputs":[]},{"cell_type":"code","metadata":{"id":"pGUzpOnQci5r","executionInfo":{"status":"ok","timestamp":1602852415910,"user_tz":-330,"elapsed":1016,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["metric_names=['accuracy','f1 score','logloss','precision','recall']"],"execution_count":229,"outputs":[]},{"cell_type":"code","metadata":{"id":"CWoeibxacuUk","executionInfo":{"status":"ok","timestamp":1602852603771,"user_tz":-330,"elapsed":1353,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["metric_models=pd.DataFrame(metrics,columns=metric_names,index=model_names)"],"execution_count":232,"outputs":[]},{"cell_type":"code","metadata":{"id":"7M4nprB3dGcY","executionInfo":{"status":"ok","timestamp":1602852611501,"user_tz":-330,"elapsed":1242,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}},"outputId":"2ceb5e3e-476a-42a3-9dc4-140df7999f5b","colab":{"base_uri":"https://localhost:8080/","height":225}},"source":["metric_models"],"execution_count":233,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>accuracy</th>\n","      <th>f1 score</th>\n","      <th>logloss</th>\n","      <th>precision</th>\n","      <th>recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Decision Tree</th>\n","      <td>0.715596</td>\n","      <td>0.786207</td>\n","      <td>9.823043</td>\n","      <td>0.826087</td>\n","      <td>0.750000</td>\n","    </tr>\n","    <tr>\n","      <th>KNN</th>\n","      <td>0.743119</td>\n","      <td>0.837209</td>\n","      <td>8.872522</td>\n","      <td>0.750000</td>\n","      <td>0.947368</td>\n","    </tr>\n","    <tr>\n","      <th>Logistic Regression</th>\n","      <td>0.807339</td>\n","      <td>0.872727</td>\n","      <td>6.654384</td>\n","      <td>0.808989</td>\n","      <td>0.947368</td>\n","    </tr>\n","    <tr>\n","      <th>Multinomial NB</th>\n","      <td>0.697248</td>\n","      <td>0.821622</td>\n","      <td>10.456936</td>\n","      <td>0.697248</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>RandomForestClassifier</th>\n","      <td>0.798165</td>\n","      <td>0.860759</td>\n","      <td>6.971232</td>\n","      <td>0.829268</td>\n","      <td>0.894737</td>\n","    </tr>\n","    <tr>\n","      <th>SupportVectorMachine</th>\n","      <td>0.807339</td>\n","      <td>0.872727</td>\n","      <td>6.654384</td>\n","      <td>0.808989</td>\n","      <td>0.947368</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                        accuracy  f1 score    logloss  precision    recall\n","Decision Tree           0.715596  0.786207   9.823043   0.826087  0.750000\n","KNN                     0.743119  0.837209   8.872522   0.750000  0.947368\n","Logistic Regression     0.807339  0.872727   6.654384   0.808989  0.947368\n","Multinomial NB          0.697248  0.821622  10.456936   0.697248  1.000000\n","RandomForestClassifier  0.798165  0.860759   6.971232   0.829268  0.894737\n","SupportVectorMachine    0.807339  0.872727   6.654384   0.808989  0.947368"]},"metadata":{"tags":[]},"execution_count":233}]},{"cell_type":"markdown","metadata":{"id":"QeiCpljTdqak"},"source":["## Final Evaluation and Saving Model"]},{"cell_type":"markdown","metadata":{"id":"TaN1GvJ7dw54"},"source":["After seeing the above table we can confidently say that SVM Performs Well"]},{"cell_type":"code","metadata":{"id":"ZxRPGcOudeAb","executionInfo":{"status":"ok","timestamp":1602852744003,"user_tz":-330,"elapsed":1336,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["import pickle"],"execution_count":234,"outputs":[]},{"cell_type":"code","metadata":{"id":"NgLXM-Y1d-SC","executionInfo":{"status":"ok","timestamp":1602852788926,"user_tz":-330,"elapsed":1137,"user":{"displayName":"Kota sai durga kamesh","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjTjqAs_XSPRluT1e_1a161LYmq1xxzr4Q-wY37=s64","userId":"02067056678749702267"}}},"source":["pickle.dump(model_svm,open(\"model_svm.pkl\",\"wb+\"),protocol=pickle.HIGHEST_PROTOCOL)"],"execution_count":235,"outputs":[]},{"cell_type":"code","metadata":{"id":"7aGBTk4ueJXI"},"source":[""],"execution_count":null,"outputs":[]}]}